Dissertations / Theses on the topic 'Channel prediction'

Knowledge of the channel over which signals are sent is of prime importance in modern wireless communications. Inaccurate or incomplete channel information leads to high error rates and wasted bandwidth and energy. Although active channel measurement is commonly used to gain channel knowledge, it can only accurately represent the channel at the time the measurement was taken, makes energy and bandwidth demands, and adds significant complexity to the radio system. Due to the highly time variant nature of wireless channels, active measurements become invalid almost as soon as they are taken, making alternative approaches to predicting future behaviour highly attractive. Such systems would allow maximum advantage to be taken of the limited bandwidth available and make significant power savings. This thesis investigates a number of complementary technologies, leading towards a channel prediction scheme suitable for mobile devices. As a first step towards channel prediction, anomaly detection is investigated within periodic wireless signals to establish when radical changes in the channel occur. In pre- vious experiments, long monotonic sequences had been observed to coincide with certain anomalies but not others when using Kullback-Leibler Divergence (KLD) analysis, possibly allowing the characterisation of anomaly types. An investigation is described to explain the origin of these features in a rigorous mathematical sense. A proof is given for the causes of the monotonic sequences, followed by a discussion of the types of signal anomaly which would underly such a feature and the value of this information. The second part describes a novel channel characterisation method which uses a class of Recurrent Neural Network (RNN) called an Echo State Network (ESN). Using this tool, a channel characterisation system can be constructed without an explicit statistical or mathematical model of the wireless environment, relying instead on observed data. This approach is much more convenient than existing models which require detailed information about the wireless system's parameters and also allows for new channel classifications to be added easily. It is able to achieve double the correct classification rate of a conventional statistical classifier, and is computationally simple to implement, making it ideal for inclusion on low-power mobile devices. Following their successful use in characterisation, ESNs are used in the final part in an investigation into channel prediction in a number of different scenarios. They were however found to be unable to produce useful predictions for all but the most trivial channel models. An alternative method is described for indoor environments using an approach inspired by ray tracing. It is simple and computationally lightweight to implement, again making it suitable for mobile devices. Simulation results show that it can outperform pilot-assisted methods by a significant margin, while not wasting bandwidth on channel measurement.

In mobile communications, channel side information at transmitters can increasecapacity. For moving relays nodes, local nodes placed on buses and trams in urbanareas, the channel state information is outdated for control delays of severalmilliseconds, as in the LTE system. Prediction of the channel based on statistic is notadequate for vehicular velocities. In this thesis, prediction made with an additionalantenna, a ``predictor antenna", placed in front of the main antenna is evaluated. Thepredictor utilises that the channel of the predictor antenna is highly correlated to thechannel experienced by the main antenna somewhat later, when the main antenna hasmoved to the position previous occupied by the predictor antenna. A normalisedcorrelation of up to 0.98 could be measured between the channels of the antennasfor an antenna separation of several wavelengths, but it was found that the closeenvironment and the antenna pattern have a big impact on the correlation. Thepredictions made with the antenna are also combined with predictions based onstatistics of past measurements from the main antenna to see if a better result can beachieved. For a prediction range of 0.5 carrier wavelengths, a prediction as good as anormalised mean square error (NMSE) of -13.9 dB could be seen. This is sufficient togive a gain in the performance when using link adaptation and opportunistic multi-userscheduling, based on channel state information at transmitter. The evaluations isbased on measurements on a 20 MHz downlink channel at 2.68 GHz.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (leaves 85-87).
Title as it appears in MIT commencement exercises program, June 2000: Satellite channels with weather-induced impairments.
Bad weather conditions, especially due to rain, cause satellites operating at high frequencies (above 10 GHz) to have significant link attenuation. Usually extra link margins are used to assure link availability. These margins cause inefficient use of precious satellite and terminal power, and unnecessarily limit data throughputs. Efficiency improvements using channel prediction and adaptation over satellite channels with weather-induced impairments are considered in this thesis. First, we consider scintillation and rain attenuation as two dominant factors for signal fading over satellite-earth paths above 10 GHz, and explore physical and mathematical modeling of the two processes. Statistical and spectral analyses of these processes using one or two pole autoregressive (AR) models yield simple linear estimators for the received signal attenuation. Using these estimators, we present results where we can predict the received signal attenuation within ±0.5 dB 1 second ahead and within ± 1.0 dB 4 seconds ahead. For adaptation, we change the signal transmission power, the modulation symbol size, and the code rate adaptively. In particular, we suggest a continuous power control and discrete rate control strategy, through which we build a set of modulation/code states, and discretely change the modulation symbol size and the code rate from state to state. Within each state, continuous power control is implemented. Several examples that use this technique and quantitative analyses of power increase and capacity are provided. The analyses indicate that there is a substantial gain in performance either in capacity and/or power consumption with the adaptive schemes.
by Jihwan Patrick Choi.
S.M.

The field of wireless communication is under massive development and the demands on the cellular system, especially, are constantly increasing as the utilizing devices are increasing in number and diversity. A key component of wireless communication is the knowledge of the channel, i.e, how the signal is affected when sent over the wireless medium. Channel prediction is one concept which can improve current techniques or enable new ones in order to increase the performance of the cellular system. Firstly, this report will investigate the concept of a predictor antenna on new, extensive measurements which represent many different environments and scenarios. A predictor antenna is a separate antenna that is placed in front of the main antenna on the roof of a vehicle. The predictor antenna could enable good channel prediction for high velocity vehicles. The measurements show to be too noisy to be used directly in the predictor antenna concept but show potential if the measurements can be noise-filtered without distorting the signal. The use of low-pass filter and Kalman filter to do this, did not give the desired results but the technique to do this should be further investigated. Secondly, a interpolation technique will be presented which utilizes predictions with different prediction horizon by estimating intermediate channel components using interpolation. This could save channel feedback resources as well as give a better robustness to bad channel predictions by letting fresh, local, channel predictions be used as quality reference of the interpolated channel estimates. For a linear interpolation between 8-step and 18-step Kalman predictions with Normalized Mean Square Error (NMSE) of -15.02 dB and -10.88 dB, the interpolated estimates had an average NMSE of -13.14 dB, while lowering the required feedback data by about 80 %. The use of a warning algorithm reduced the NMSE by a further 0.2 dB. It mainly eliminated the largest prediction error which otherwise could lead to retransmission, which is not desired.

The number of radio systems operating in the 2.4 GHz band is rising as a result of increased usage of wireless technologies. Since such devices interfere with one another, satisfactory co-existence becomes important. Several techniques serve to reduce the interference. Included among these are frequency hopping (FH) and power-control. This report focuses only on FH, and particularly on methods that make FH schemes adaptive. An FH scheme is adaptive if it responds to the noise and fading by avoiding channels that are unfit for transmission. An example of such a scheme is already implemented in an audio transceiver, the nRF24Z1, manufactured by Nordic Semiconductor. That transceiver provides the framework for this study, and the main objective is to suggest improvements to its FH algorithm. Better performance is particularly interesting in high quality audio streaming because such transmissions generally have strict real time requirements. Thus, the time to retransmit corrupted data is limited, and measures to reduce the impact of interference and fading are desired. The FH scheme implemented in the nRF24Z1 works broadly as follows: If a channel distorts more than a certain share of the transmitted data, it is extracted from the FH routine and listed as banned for usage. The ban list has room for maximum 18 out of 38 channels and can therefore filter out significant parts of the spectrum. If the system identifies more poor channels than the list can hold, the oldest channel in the ban list is released, and the newly identified one takes its place. In a scenario where noise and deep fades come to occupy a rather stable group of channels, the banned channels will match the unsuited parts of the spectrum quite accurately, and the scheme performs well. However, when the noise and fading is changing, maybe quickly and non-periodically, the performance drops significantly. The reason is that channels are banned only after they have caused trouble, which has two negative effects. Firstly, it is likely that the bulk of the transmitted data was distorted, and the need for retransmission can therefore be large. Secondly, since the transmission conditions are changing, the ban list becomes outdated and reflects the actual interference and fading poorly. Therefore, in this report, the possibility of predicting poor channels in order to avoid them beforehand, is investigated. For the purpose of prediction, small test packets are transmitted. In short, the principle of operation is that if a test packet is readable at the receiver, the channel is used. Otherwise it is avoided. Computer simulations indicate that this technique improves transmission conditions and reduces the need for retransmission when the noise and fading change significantly. Large changes are indeed common in practice. They occur, for example, if a broadband interferer is switched off or greatly varies its output power. Plainly, they could also come about when objects move. Despite promising simulations, channel testing does not come without side effects. An audio streaming system like the nRF24Z1 must secure a certain flow of data to avoid audible errors. If prediction algorithms are to secure that flow, a compromise must be made: the more time a system spends on channel testing, the less time remains for transmission of data. Therefore, at some point, testing must be terminated to leave room for the real job. In consequence, the key issue of finding the best trade-off between testing and transmission must be addressed. This report presents three adaptive FH schemes that approach that issue in their own manner. The performance of the proposed prediction schemes has been investigated using a channel model for the ISM band (Industrial, Medical, and Scientific). It is coded and developed in MATLAB. The model mimics the effects of a real mobile channel quite well, and this inspires non-negligible confidence in the simulation results.

One of the currently explored strategies for interference avoidance and improving Signal to Noise Ratio (SNR) for mobile communication systems is Coordinated MultiPoint (CoMP) transmission. The general idea of the strategy is to let two or more base stations serve the same user. Due to delay factors, the channels from each serving base station needs to be predicted to obtain an adaptive CoMP system. In this thesis, a user interface is created to act as an experimental platform for a set of measured downlink channel data. The user interface supports editing of the channel data, model estimation, Kalman filtering and prediction and evaluation of the channel statistics. The user interface and the measured channel downlink data is then used to examine how well we can predict the weakest channel in a CoMP setup with three base stations. The predictions are carried out using an m-step Kalman predictor which uses an AR4 model, estimated from previous channel data. For the investigation, the user moves at pedestrian speed and the signals from the three different base stations use orthogonal Common Reference Signals (CRS). A comparison of different CRS patterns is also included in the investigation. It is concluded that 5 ms predictions of the weakest channel achieves a normalized mean squared error (NMSE) of -8 dB or lower provided that the weakest signal has an SNR of at least 5 dB and is no more than 15 dB lower than the combined received signal. Additionally, it is found that predictions are more accurate for CRS patterns spread over time than over subcarriers.

ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California
Adaptive modulation is a communication technique capable of maximizing throughput while guaranteeing a fixed symbol error rate (SER). However, this technique requires instantaneous channel state information at the transmitter. This can be obtained by predicting channel states at the receiver and feeding them back to the transmitter. Existing algorithms used to predict single-input single-output (SISO) channels with recurrent neural networks (RNN) are extended to multiple-input multiple-output (MIMO) channels for use with adaptive modulation and their performance is demonstrated in several examples.

The characterisation of the indoor radio channel has been an active area of research in the last decades, and this is likely to continue with the increasing importance of wireless techniques for the provision of connectivity within homes and offices. This thesis gives a survey of existing models for the indoor radio channel, noting that sitespecific predictions are often of limited use owing to the difficulty of determining accurate details ofthe indoor environment. While ray tracing models, for instance, are potentially capable of offering highly accur~te prediction, this promise is seldom fulfilled in practice owing to the difficulty of capturing the necessary input data for such models. As a consequence, statistical treatments ofthe indoor channel are popular, and two such models for the temporal response ofthe wideband channel are discussed in some detail. These models, however, rely on the use of empirical parameters that will either represent only the generality of buildings, or will need to be determined by measurement for each specific case. An alternative model was therefore sought which combined physical and statistical elements to introduce a greater degree of site-specificity. The initial modelling reported in this thesis took, as its basis, the methods developed within the acoustic community for the prediction of impulse response within reverberant rooms. The thesis then proposes a new model for the prediction ofthe average power delay profile (PDP) within a room, taking the extreme room dimensions as parameters to allow the accommodation of site-specific detail. A measurement campaign, using a channel sounder developed for the purpose, is described, and the results compared with the predictions offered by the new model. Finally, the thesis suggests ways in which the new model might be used as a component of other, more general, models for the indoor radio channel.

An examination was carried out to determine the conveyance behaviour of overbank flow in meandering two-stage channel systems. Eleven influential parameters were identified namely sinuosity, aspect ratio, cross-sectional shape and bank slope of the main channel, relative boundary roughness of floodplain to main channel, floodplain longitudinal slope, meander belt width relative to floodplain width, sinuosity of the floodplain bank, relative overbank flow depth, system scale and lateral slope of the floodplain. The first ten of the eleven parameters were examined. Observations were made of the coherent flow structure of the floodplain and main channel systems, which influences energy losses. The effect of each of the influential parameters is quantified through a non-dimensional discharge function F^* which is the ratio of the actual discharge in a two-stage channel to a theoretical discharge aggregated for three cross-section zones, the main channel, the floodplain within the meandering channel and the floodplain outside the meander belt. The effect of each parameter on the energy losses in meandering two-stage channel flows for the case involving straight floodbanks and a floodplain without cross-fall are analysed in terms of Darcy-Weisbach resistance coefficients using the Prandt-von Karman resistance relationship and treating the system as a whole. Flow domains are defined in the first of which viscosity and roughness are influential and in the second flow resistance is independent of viscosity. A design approach is presented for predicting the conveyance capacity in each of these domains and is based on small-scale data obtained at the Universities of Aberdeen and Glasgow and large-scale data from the UK Flood Channel Facility (UK-FCF). This approach was applied to the available independent laboratory data along with the James and Wark (1992) method. The author's approach was found to give good predictions of conveyance capacity. This approach was also applied to River Roding field data. The floodplain roughness which varies throughout the year and is difficult to estimate, is shown to be the most significant source of energy loss and is environmentally sensitive in natural meandering two-stage rivers.

This thesis examines the benefits of using adaptive modulation and coding in terms of spectral efficiency and probability of bit error. Specifically, we examine the performance enhancement made possible by using linear prediction along with channel estimation in conjunction with adaptive modulation. We begin this manuscript with basic fundamentals of our study, followed by a detailed view of simulations, their results, and our conclusions from them. The study includes simulations in slow and moderately fast flat fading Rayleigh channels. We present our findings regarding the advantages of using predictive measures to foresee the state of the channel and make adjustments to transmissions accordingly. In addition to finding the general advantages of channel prediction in adaptive modulation, we explore various ways to adjust the prediction algorithm when we are faced with high Doppler rates and fast fading. By the end of this work, we should have a better understanding of when channel prediction is most valuable to adaptive modulation and when it is weakest, and how we can alleviate the problems that prediction will have in harsh environments.
Master of Science

In multi-user multiple input multiple output orthogonal frequency division multiplexing downlink system, it is important to have an accurate channel state information at the base-station in order to minimize the inter-user interference. However, when the channel changes rapidly, the available channel state information at the base-station can be outdated, causing performance loss. In this research, we propose to use linear adaptive filtering algorithms, such as normalized least mean squares and recursive least squares to predict the channel state information at the base-station to improve the bit-error-rate performance of the downlink system. This research further validates the superior performance of these channel prediction algorithms over the conventional linear extrapolation method using the actual channel measurement data.

Prediction of the rapidly fading envelope of a mobile radio channel enables a number of capacity improving techniques like fast resource allocation and fast link adaptation. This thesis deals with linear prediction of the complex impulse response of a channel and unbiased quadratic prediction of the power. The design and performance of these predictors depend heavily on the correlation properties of the channel. Models for a channelwhere the multipath is caused by clusters of scatterers are studied. The correlation for the contribution from a cluster can be approximated as a damped complex sinusoid. A suitable model for the dynamics of the channel is an ARMA-process. This motivates the use of linear predictors.

A limiting factor in the prediction are the estimation errors on the observed channels. This estimation error, caused by measurement noise and time variation, is analyzed for a block based least squares algorithm which operates on a Jakes channel model. Efficient noise reduction on the estimated channel impulse responses can be obtained with Wienersmoothers that are based on simple models for the dynamics of the channel combined with estimates of the variance of the estimation error.

Power prediction that is based on the squared magnitude of linear prediction of the taps will be biased. Hence, a bias compensated power predictor is proposed and the optimal prediction coefficients are derived for the Rayleigh fading channel. The corresponding probability density functions for the predicted power are also derived. A performance evaluation of the prediction algorithm is carried out on measured broadband mobile radio channels. The performance is highly dependent on the variance of the estimation error and the dynamics of the individual taps.

In an optimal power control scheme for a Code Division Multiple Access (CDMA) system all mobile stations signals should arrive to the base station at equal power. If not, stronger singals may cause too much interference and block out weaker ones. Commonly used power control schemes utilizes the Signal to Interference Ratio (SIR) to design a Power Control Command (PCC) to adjust the transmit power of the mobile station. A significant problem within the conventional methods is the slow SIR recovery due to deep channel fades. Conventional methods base the PCC on the previous channel state when in fact, the channel state may have significantly changed when transmission occurs. These channel changes may cause the SIR to drop or rise drastically and lead to uncontrollable Multi Access Interference (MAI) resulting in power escalation and making the system unstable. In order to overcome power escalation and improve the recovery from deep fades a novel power control method has been developed. Based on Linear Quadratic Control and Kalman filtering for channel prediction this method designs the PCC based on the coming channel state instead of the current. This optimizes the PCC for the channel state where transmission occurs. Simulations show that this control scheme outperforms previous methods by making the impacts of the deep fades less severe on the SIR and also improves the overall SIR behaviour.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2001.
"February 2001."
Includes bibliographical references (leaves 17-19).
Common methods of extracting representations of drainage networks from raster digital elevation models for hydrological and geomorphological applications are similar to a class of image processing methods known as grayscale watershed algorithms. These algorithms partition a field of scalar values into connected regions based on a local minimum associated with each region. A related class of image processing algorithms, known as 2-dimensional skeletonization algorithms, reduce a planar shape to a one-dimensional, connected, graph-like structure, called a skeleton, that maintains significant information about the properties of the original shape. The morphological similarity between the skeleton of a region and a drainage network suggest that skeletonization algorithms might be used to relate basin shape to the drainage network within the basin. This idea was examined by applying two 2-dimensional skeletonization algorithms to two drainage basin boundary shapes extracted from digital elevation models to attempt to predict stream channel locations within the basin. The skeletons computed for the two basins studied did not predict the location of principal channels in the interiors of the basins studied. This is due, at least in part, to the fact that these two dimensional algorithms only consider symmetry with respect to plan view basin shape, with no consideration made of relative elevations along basin boundaries or position of the boundary points with respect to the basin outlet. In convex outward salients of the upper reaches of the two basins studied, the position and planform of computed skeletons agree reasonably well with the upper reaches of drainage networks derived from the digital elevation model. This observation suggests a relationship between basin boundary shape and the location and form of the channel network, at least in the neighborhood of the boundary in upper portions of the basins. A brief review of recent results from computational geometry and image analysis suggest several possible methods of extending this analysis to incorporate relative elevation along the boundary and orientation of the boundary with respect to the basin outlet, and possibly resolving this question.
by Robert J. Fleming, Jr.
S.M.

Tailings (mining waste) disposal is a significant consideration for the mining industry, with the majority of the ore processed in most mining operations ending up as tailings. This creates large volumes of tailings, which must be handled and stored responsibly to avoid potential environmental catastrophes. The most common form of tailings storage facility is the impoundment, where tailings are contained within a basin, with beaches forming around the perimeter of the impoundment and a pond standing in the middle. A relatively new method of tailings storage is to create a 'stack', whereby the tailings solids form a large heap, with the discharge of tailings slurry from the apex of the heap. It is of significant value for mine operators and tailings engineers to be able to predict the shape of the beach that forms in either of these disposal scenarios. The key to being able to do this relies on a method of prediction of the beach slope. The aim of this work is to develop a method of tailings beach slope prediction for tailings slurries that are sub-aerially discharged from a pipe. In this thesis a literature review is undertaken, investigating existing methods for the prediction of tailings beach slopes. These methods are validated against relevant industrial and experimental data. Two separate phases of experimental work have taken place in an effort to investigate tailings deposition behaviour, one at mine sites and the other in a laboratory on a small scale. Three new tailings beach slope prediction models are presented; a simple empirical model enabling quick approximate predictions; an a priori tailings beach slope prediction model based on existing theories of open channel flow, sediment transport and rheology, which is more powerful due to the greater degree of theory in its foundation; and a new semi-empirical model that shares some of the theoretical aspects of the a priori model but offers better predictions due to its empirical calibration to the experimental data. The experimental results, along with 3 other independently collected sets of relevant industrial and experimental data, are used to validate the beach slope prediction models found in the literature, as well as the new beach slope models presented in this thesis. Statistical evaluation of the performance of all of these models is presented to enable comparison. Finally, a new beach shape model is presented for the three dimensional geometric forecasting of the beach surface of a tailings stack. Historic tailings discharge data is run through the beach shape model, and the shapes predicted by the model are compared with aerial survey data of a real tailings stack for validation of the shape model. This work not only presents a new method of tailings stack shape prediction, but also a plausible theory for explaining the concavity of tailings beaches. The stack shape model also has the potential to be developed further for the three dimensional modelling of tailings beaches formed in other types of storage facilities, such as impoundments or valleys.

With commercial deployment of the Citizens Band Radio Service commencing in the last quarter of 2018, efforts are in progress to improve the efficiency of the Spectrum Access System (SAS) functions. An area of concern as identified in recent field trials is the timebound evacuation of unlicensed secondary users from a frequency band by the SAS on the arrival of an incumbent user. In this thesis, we propose a way to optimize the evacuation process by reducing the number of secondary spectrum grant revocations to be performed. The proposed work leverages knowledge of incumbent user spectrum occupancy pattern obtained from historical spectrum usage data. Using an example model trained on 48 hours of an incumbent user transmission information, we demonstrate prediction of future incumbent user spectrum occupancy for the next 15 hours with 94.4% accuracy. The SAS uses this information to set the time validity of the secondary spectrum grants appropriately. In comparison to a case where spectrum grants are issued with no prior knowledge, the number of revocations declines by 87.5% with a 7.6% reduction in channel utilization. Further, the proposed technique provides a way for the SAS to plan ahead and prepare a backup channel to which secondary users can be redirected which can reduce the evacuation time significantly.
Master of Science
Studies on spectrum occupancy show that, in certain bands, licensed incumbent users use the spectrum only for some time or only within certain geographical limits. The dynamic spectrum access paradigm proposes to reclaim the underutilized spectrum by allowing unlicensed secondary users to access the spectrum opportunistically in the absence of the licensed users. In the United States, the Federal Communications Commission (FCC) has identified 150 MHz of spectrum space from 3550-3700 MHz to implement a dynamic spectrum sharing service called the Citizens Broadband Radio Service (CBRS). The guiding principle of this service is to maximize secondary user channel utilization while ensuring minimal incumbent user disruption. In this study, we propose that these conflicting requirements can be best balanced in the Spectrum Access System (SAS) by programming it to set the time validity of the secondary license grants by taking into consideration the incumbent spectrum occupancy pattern. In order to enable the SAS to learn incumbent spectrum occupancy in a privacy-preserving manner, we propose the use of a deep learning model, specifically the long-short term memory (LSTM). This model can be trained by federal agencies on historical incumbent spectrum occupancy information and then shared with the SAS in a secure manner to obtain prediction information about possible incumbent activity. Then, using the incumbent spectrum occupancy information from the LSTM model, the SAS could issue license grants that would expire before expected arrival time of incumbent user, thus minimizing the number of revocations on incumbent arrival. The scheme was validated using simulations that demonstrated the effectiveness of this approach in minimizing revocation complexity.

With the increased usage of optical wireless communication, finding appropriate parameters for reliable transmission and providing efficient channel performance have become of challenging interest in research and industry. This has been a strong motivation to examine and develop methods and techniques to find suitable link parameters to increase the channel availability. This thesis is mainly concerned with designing, implementing and adapting intelligent algorithms to solve for parameter selection, channel prediction, and channel adaptation in dynamic optical wireless channels. The problem could be solved with other methods such as binary and sequential search; however, intelligent systems have the ability to find optimal results with more reliability, time efficiency and increased flexibility. The research focuses on single and multi-objective selection techniques using application-specific genetic algorithm (ASGA) in the outdoors line-of-sight (LOS) optical wireless channel where parameters have different effects on the channel performance and may affect the behaviour of other channel parameters. The technique is well-established at pre-installation stages of the channel, and could be also applied at run-time if a reconfigurable hardware is installed. An intelligent system, which uses a genetic algorithm predicted and optimized optical wireless channel in the (LOS) field, is presented. The prediction technique is proposed to estimate the bit error rate (BER) at the receiver, and suggests appropriate selection of link parameters. In this research, the work is developed based on on-off keying (OOK) modulation, and makes use of different weather conditions for channel modeling. A first attempt is made with a GA-based selection for transmission wavelengths (700nm to 1600nm), the overall deterministic attenuations being estimated by a visibility model, where the changes in visibility decide about the wavelength control margin. The research is then extended to consider various external link parameters scaled by look-up tables that meet the optical wireless industry. It shows that the transmission power should not always be the only costin the channel, and there are other parameters worthy of control. Principal Component Analysis is applied targeting the ASGA selected datasets to extract the contribution of each parameter to the output, and the implicit relations that exist among data sets to achieve a certain bit-error-rate. An Artificial Neural Network (ANN) is then applied to the channel for BER prediction; this may also validate the pre-installation advice done by PCA. Finally, a two-stage modelling using a neuro-fuzzy hybrid algorithm used for adapting the channel by monitoring the link range and total attenuations in the channel. Through analysing the simulation results using these intelligent systems algorithms, the thesis aims at providing maximum utilization of channel parameters for achieving optimum channel performance and increased availability under the application of various intelligent systems, which demonstrate their efficiency and effectiveness as compared with other techniques.

This thesis is focused on a study on modeling and measurement of the indoor radio and infrared channels. Both channels have been studied, compared and their vital differences identified. Initially, an infrared channel model was developed that was not similar to any existing models for the infrared domain. The wireless diffuse infrared channel is solely used indoors and is usually confined within a room. Conventional channel models are described, but their disadvantage is heavy time and processor requirements. A new model is introduced, in which the approach is different from the traditional methods in the way that it discretises the delay range instead of the physical characteristics of the environment. The new model offers accurate results without the increased time and processor requirements compared with traditional techniques. Following the characterisation of the infrared channel, a wideband radio propagation campaign took place in two different buildings that allowed valuable insight into the mobile radio channel. Time domain analysis of the measurement results allowed the careful study of the radio channel and produced interesting results as far as RMS delay spread and Power Delay Statistics are concerned. It has been shown that the RMS delay spread is not always dependent on antenna separation, while it was found to be highly dependent on the clutter present on the measurement environment. The infrared model was finally converted to account for radio propagation. Traditional channel models for indoor propagation prediction are described, while the major differences of the infrared and radio channel are mentioned. The radio channel prediction benefits from the accuracy of the infrared model, where a very high accuracy is necessary in order to predict the effect of scattering. A simple measurement campaign has been introduced in order to validate the results of the simulation tool and a comparison with the most important wideband channel models has been performed, along with higher frequency measurements where scattering is more important. The results present a good fit to the measurements and models in the literature, and empirical conclusions relative to the scattering characteristics of the radio channel are drawn from these comparisons.

In this thesis a new approach for characterisation of digital mobile radio channels is investigated. The new approach is based on recognition of the fact that while the fading which is characteristic of the mobile radio channel is very rapid, the processes underlying this fading may vary much more slowly. The comparative stability of these underlying processes has not been exploited in system designs to date. Channel models are proposed which take account of the stability of the channel. Estimators for the parameters of the models are proposed, and their performance is analysed theoretically and by simulation and measurement. Bounds are derived for the extent to which the mobile channel can be predicted, and the critical factors which define these bounds are identified. Two main applications arise for these channel models. The first is the possibility of prediction of the overall system performance. This may be used to avoid channel fading (for instance by change of frequency), or compensate for it (by change of the signal rate or by power control). The second application is in channel equalisation. An equaliser based on a model which has parameters varying only very slowly can offer improved performance especially in the case of channels which appear to be varying so rapidly that the convergence rate of an equaliser based on the conventional model is not adequate. The first of these applications is explored, and a relationship is derived between the channel impulse response and the performance of a broadband system.

En els sistemes de comunicacions on el transmissor disposa de certa informació sobre l'estat del canal (CSI), es possible dissenyar esquemes lineals de precodificació que assignin la potència de manera òptima induint guanys considerables, sigui en termes de capacitat, sigui en termes de la fiabilitat de l'enllaç de comunicacions. A la pràctica, aquest coneixement del canal mai és perfecte i, per tant, el senyal transmès es veurà degradat degut al desajust entre la informació que el transmissor disposi del canal i el seu estat real.

En aquest context, aquesta tesi estudia dos problemes diferents però alhora estretament relacionats: el disseny d'un esquema pràctic de seguiment del canal en transmissió per canals variants en temps, i el disseny d'esquemes lineals de precodificació que siguin robustos a la incertesa del canal.

La primera part de la tesi proposa el disseny d'un esquema de seguiment de canal que, mitjançant un enllaç de retorn de baixa capacitat, proporcioni al transmissor una informació acurada sobre el seu estat. Històricament, aquest tipus d'esquemes han rebut fortes crítiques degut a la gran quantitat d'informació que és necessari transmetre des del receptor cap el transmissor. Aquesta tesi, doncs, posa especial èmfasi en el disseny d'aquest canal de retorn. La solució que es proposa, basada en el filtre de Kalman, utilitza un esquema que recorda al transmissor DPCM. Les variacions del canal són tractades mitjançant dos predictors lineals idèntics situats en el transmissor i en el receptor, i un canal de retorn que assisteix el transmissor amb l'error de predicció. L'interès d'aquest esquema diferencial és que permet seguir les variacions del canal amb només dos o quatre bits per coeficient complex, fins i tot en canals ràpidament variants.

La resta de la tesi cobreix el segon objectiu, l'estudi de diferents esquemes d'assignació de potències quan el coneixement del canal en transmissió no és perfecte. El problema es planteja per a un sistema MIMO OFDM com a formulació més general, incloent els casos d'una sola antena, de l'esquema beamforming i del canal multiplicatiu com a casos particulars.

Primerament s'ha plantejat l'optimització dels criteris de mínim error quadràtic mig (MMSE) i mínima BER sense codificar. La innovació en el treball presentat a la tesi, respecte a altres treballs que segueixen els mateixos criteris de disseny, ha estat la formulació Bayesiana del problema per al disseny dels algoritmes robustos.

La tesi continua amb el plantejament d'estratègies robustes d'assignació de potència destinades a minimitzar la BER codificada. Per aquesta tasca s'han utilitzat criteris de teoria de la informació. Possiblement una de les principals contribucions d'aquesta tesi ha estat el plantejament del cut-off rate com a paràmetre de disseny. Aquest criteri s'introdueix com alternativa a la capacitat de canal o a la informació mutual per al disseny del transmissor quan s'inclou codificació de canal.



La ultima part de la tesi proposa un interleaver adaptatiu de baixa complexitat que, utilitzant el coneixement del canal disponible en el transmissor, assigna estratègicament els bits no només per combatre les ràfegues d'errors, sinó també per lluitar contra els esvaïments que puguin presentar les diferents portadores del canal per a una realització concreta. El disseny d'aquest interleaver, anomenat "interleaver RCPC" està basat en els codis Rate-Compatible Punctured Convolutional Codes. Com s'il·lustra a partir del resultats numèrics, l'ús d'aquest interleaver millora les prestacions dels algoritmes quan es comparen amb les que s'obtindrien si s'utilitzes un interleaver de bloc o un interleaver pseudo-aleatori.
When the transmitter of a communication system disposes of some Channel State Information (CSI), it is possible to design linear precoders that optimally allocate the power inducing high gains either in terms of capacity or in terms of reliable communications. In practical scenarios, this channel knowledge is not perfect and thus the transmitted signal suffers from the mismatch between the CSI at the transmitter and the real channel.

In that context, this thesis deals with two different, but related, topics: the design of a feasible transmitter channel tracker for time varying channels, and the design of optimal linear precoders robust to imperfect channel estimates.

The first part of the thesis proposes the design of a channel tracker that provides an accurate CSI at the transmitter by means of a low capacity feedback link. Historically, those schemes have been criticized because of the large amount of information to be transmitted from the receiver to the transmitter. This thesis focuses, thus, the attention in an accurate design of the return link. The proposed solution is based on the Kalman filter and follows a scheme that reminds the well known DPCM transmitter. The channel variability is processed by two identical linear predictors located at the transmitter and at the receiver, and a feedback link that assists the transmitter with the prediction error. The interest of this differential scheme is that allows to track the channel variations with only two or four bits per complex channel coefficient even in fast time-varying channels.

The rest of the thesis covers the second topic, studying different robust power allocation algorithms when the CSI is not perfectly known at the transmitter. For the sake of generality, the problem is formulated for the general MIMO OFDM case, encompassing the single antenna transmission, the beamforming schemes and the frequency-flat fading channels as particular cases.

First, the minimum MSE and the minimum uncoded BER parameters are chosen to be optimized, evaluating the performance of the algorithms in terms of uncoded BER. The basic novelty with respect to previous works that considers the same strategies of design is the proposal of a Bayesian approach for the design of the robust algorithms.

Next the study is extended by proposing robust power allocation strategies focused on the minimization of the coded BER. For this purpose, information-theoretic criteria are used. Probably, one of the main contributions in the thesis is the proposal of the cut-off rate as a parameter of design whose maximization is directly related to the coded BER. This criterion is introduced as an alternative to the channel capacity and the mutual information for the design of optimal transceivers in the presence of any channel coding stage.






The last part of the thesis proposes a low complexity adaptive interleaver that, making use of the CSI available at the transmitter, reallocates the bits not only to combat the bursty channel errors but also to combat the specific distribution of the faded subcarriers as a function of the channel response. The design of this interleaver, named as "RCPC interleaver", is based on the Rate-Compatible Punctured Convolutional Codes. As shown by numerical results, the use of this interleaver improves the performance of the algorithms when they are compared with the classical block interleavers and pseudo-random interleavers.

Abstract This thesis seeks to develop a robust semi-analytical performance prediction method for an advanced iterative receiver that processes spatially multiplexed signals that have propagated through frequency-selective receive correlated multiple-input multiple-output (MIMO) wireless communication channels. In a change of perspective, the proposed performance prediction methods are applied at the transmitter, which seeks to attain a target frame error rate (FER) either by adaptive power control or by adaptive modulation and coding (AMC). The performance prediction scheme utilises the statistical properties of the channel—namely noise variance, number of separable propagation paths and the eigenvalues of the receive correlation matrix—to predict the signal-to-interference-plus-noise ratio (SINR) at the output of a frequency domain soft interference cancellation minimum mean square error equaliser. The SINR distribution is used to derive the distribution of the variance of the log-likelihood ratios (LLRs) at the output of a soft symbol-to-bit demapper. Mutual information transfer charts establish a bijective relationship between the variance of the LLRs and mutual information. A 3rd Generation Partnership Project compliant turbo code is assumed. Since the decoder operates independently from the channel, its extrinsic information transfer (EXIT) charts can be simulated in advance. By utilising the approximate LLR variance distribution of the demapped equaliser output, it is possible to evaluate the probability of an intersection between an equaliser chart associated with a random channel realisation and a fixed decoder chart. This probability provides the FER. Since the proposed performance prediction method does not require any instantaneous channel state information, it can be applied at the transmitter side as a robust link adaptation scheme. In adaptive transmission power control, the modulation order and code rate are fixed. By iteratively adjusting transmission power, the transmitter attempts to find an equaliser output LLR variance distribution that reaches a specified target FER. In AMC, transmission power is fixed. The equaliser output's LLR variance distribution is determined by the modulation order, while the decoder chart's position is determined by the code rate. The transmitter iteratively adjusts the code rate and attempts to find a modulation order and code rate pairing that reaches the target FER. For vertically encoded spatially multiplexed systems, the adaptive transmission power control and AMC schemes are complemented by adaptive repeat redundancy and incremental redundancy hybrid automatic repeat request (HARQ) techniques, respectively
Tiivistelmä Työn tavoitteena on kehittää luotettava semianalyyttinen suorituskyvyn ennustusmenetelmä tehokkaalle iteratiiviselle vastaanottimelle, joka käsittelee taajuusselektiivisen, vastaanotinpäässä tilakorreloituneen moniantennikanavan kautta kulkeneita tilakanavoituja signaaleja. Toisessa vaiheessa esitettyjä ennustusmenetelmiä hyödynnetään mukauttamalla lähetystehoa tai modulaatioastetta ja koodisuhdetta (adaptive modulation and coding [AMC]), samalla säilyttäen tavoitteeksi asetetun kehysvirhesuhteen (frame error rate [FER]). Suorituskyvyn ennustusmenetelmä hyödyntää kanavan tilastollisia ominaisuuksia – kohinan varianssia, eroteltavien etenemispolkujen lukumäärää sekä vastaanottimen korrelaatiomatriisin ominaisarvoja – ennustaakseen signaali–kohina-plus-interferenssisuhteen (signal-to-interference-plus-noise ratio [SINR]) jakauman taajuustasossa toimivan, häiriötä poistavan pienimmän keskineliösumman kanavakorjaimen lähdössä. SINR-jakaumasta johdetaan pehmän symboleista biteiksi -muunnoksen jälkeisten logaritmisten bittitodennäköisyyksien suhdelukujen (log-likelihood ratio [LLR]) jakauma. Keskinäisinformaation siirroskartat perustuvat LLR:ien varianssin sekä keskinäisinformaation väliseen bijektiivisyyteen. Informaatio on kanavakoodattu 3rd Generation Partnership Project -standardin mukaisella turbokoodilla. Turbodekooderin toiminta on kanavasta riippumatonta, joten dekooderin lisäinformaation siirroskartat (extrinsic information transfer [EXIT] charts) voidaan simuloida itsenäisesti. Hyödyntämällä kanavakorjaimen lähdön pehmeiden bittipäätösten LLR:ien varianssin jakaumaa, on mahdollista arvioida millä todennäköisyydellä korjaimen satunnaisen kanavarealisaation siirroskartta leikkaa dekooderin siirroskartan. Tämä todennäköisyys voidaan tulkita kehysvirhesuhteeksi. Koska suorituskyvyn ennustusmenetelmä ei vaadi hetkellistä tietoa kanavan tilasta, sitä voidaan hyödyntää lähetyksen mukautuksessa. Mukautuvassa tehonsäädössä modulaatio ja koodisuhde eivät muutu. Lähetin pyrkii iteratiivisella tehonsäädöllä löytämään korjaimen lähdölle LLR-jakauman, joka tuottaa halutun kehysvirhesuhteen. Mukautuvassa modulaation ja koodisuhteen valinnassa lähetysteho säilyy vakiona. Modulaatioaste vaikuttaa korjaimen lähdön LLR-jakaumaan ja koodisuhde dekooderin siirroskartan muotoon. Iteratiivisesti koodisuhdetta säätämällä lähetin pyrkii löytämään modulaation ja koodisuhteen yhdistelmän, joka saavuttaa tavoitellun kehysvirhesuhteen. Vertikaalisesti tilakanavoiduissa järjestelmissä mukautuvaa tehonsäätöä täydennetään lähetystehoa mukauttavilla uudellenlähetyksillä, kun taas mukautuvaa modulaation ja koodisuhteen valintaa täydennetään puolestaan koodisuhdetta pienentävillä automattisilla uudelleenlähetyspyynnöillä (hybrid automatic repeat request [HARQ])

With the accessibility to generous spectrum and development of high gain antenna arrays, wireless communication in higher frequency bands providing multi-gigabit short range wireless access has become a reality. The directional antennas have proven to reduce losses due to interfering signals but are still exposed to blockage events. These events impede the overall user connectivity and throughput. A mobile blocker such as a moving vehicle amplifies the blockage effect. Modelling the blockage effects helps in understanding these events in depth and in maintaining the user connectivity. This thesis proposes the use of a four state channel model to describe blockage events in high-frequency communication. Two deep learning architectures are then designed and evaluated for two possible tasks, the prediction of the signal strength and the classification of the channel state. The evaluations based on simulated traces show high accuracy, and suggest that the proposed models have the potential to be extended for deployment in real systems.
Med tillgängligheten till generöst spektrum och utveckling av antennmatriser med hög förstärkning har trådlös kommunikation i högre frekvensband som ger multi-gigabit kortdistans trådlös åtkomst blivit verklighet. Riktningsantennerna har visat sig minska förluster på grund av störande signaler men är fortfarande utsatta för blockeringshändelser. Dessa händelser hindrar den övergripande användaranslutningen och genomströmningen. En mobil blockerare såsom ett fordon i rörelse förstärker blockeringseffekten. Modellering av blockeringseffekter hjälper till att förstå dessa händelser på djupet och bibehålla användaranslutningen. Denna avhandling föreslår användning av en fyrstatskanalmodell för att beskriva blockeringshändelser i högfrekvent kommunikation. Två djupinlärningsarkitekturer designas och utvärderas för två möjliga uppgifter, förutsägelsen av signalstyrkan och klassificeringen av kanalstatusen. Utvärderingarna baserade på simulerade spår visar hög noggrannhet och föreslår att de föreslagna modellerna har potential att utökas för distribution i verkliga system.

Extreme rainfall events associated with global warming are likely to produce an increasing number of flooding scenarios. A large magnitude of hydrologic events can often result in submerged orifice flow (also called pressure flow) or embankment and bridge overtopping flow, in which the foundation of a bridge is subjected to severe scour at the sediment bed. This phenomenon can cause bridge failure during large floods. However, current laboratory studies have focused on only cases of free-surface flow conditions, and they do not take bridge submergence into account. In this study, abutment scour experiments were carried out in a compound channel to investigate the characteristics of abutment scour in free-surface flow, submerged orifice flow, and overtopping flow cases. Detailed bed contours and three components of velocities and turbulent intensities were measured by acoustic Doppler velocimeters. The results show that the contracted flow around an abutment because of lateral and/or vertical contraction and local turbulent structures at the downstream region of the bridge are the main features of the flow responsible for the maximum scour depth around an abutment. The effects of local turbulent structures on abutment scour are discussed in terms of turbulent kinetic energy (TKE) profiles measured in a wide range of flow contraction ratios. The experimental results showed that maximum abutment scour can be predicted by a suggested single relationship even in different flow types (i.e., free, submerged orifice, and overtopping flow) if the turbulent kinetic energy and discharge under the bridge can be accurately measured.

As there is a rapid growth in the field of wireless communications, the demand for various multimedia services is also increasing. The data that is being transmitted suffers from distortions through source encoding and transmission over errorprone channels. Due to these errors, the quality of the content is degraded. There is a need for service providers to provide certain Quality of Experience (QoE) to the end user. Several methods are being developed by network providers for better QoE.The human tendency mainly focuses on distortions in the Region of Interest(ROI) which are perceived to be more annoying compared to the Background(BG). With this as a base, the main aim of this thesis is to get an accurate prediction quality metric to measure the quality of the image over ROI and the BG independently. Reduced Reference Image Quality Assessment (RRIQA), a reduced reference image quality assessment metric, is chosen for this purpose. In this method, only partial information about the reference image is available to assess the quality. The quality metric is measured independently over ROI and BG. Finally the metric estimated over ROI and BG are pooled together to get aROI aware metric to predict the Mean Opinion Score (MOS) of the image.In this thesis, an ROI aware quality metric is used to measure the quality of distorted images that are generated using a wireless channel. The MOS of distorted images are obtained. Finally, the obtained MOS are validated with the MOS obtained from a database [1].It is observed that the proposed image quality assessment method provides better results compared to the traditional approach. It also gives a better performance over a wide variety of distortions. The obtained results show that the impairments in ROI are perceived to be more annoying when compared to the BG.

This research explored quantitative relationships (QSPKR) between different molecular descriptors and pertinent, systemic PK properties for 14 calcium channel blockers (CCB). Physicochemical properties (PC) such as molecular weight (MW), molar volume (MV), calculated logP (clogP), pKa, calculated logD7.4 (clogD), % ionized at pH 6.3 and pH 7.4, hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), and number of rotatable bonds (nRot) were chosen as possible predictor variables for systemic PK properties for CCB, obtained from pertinent literature, assessing the PK of CCB after intravenous administration to healthy humans. All PC properties and molecular descriptors were computed using ACD-solubility/DB 12.01. Total body clearance (CLtot), steady-state volume of distribution (Vdss), total area under the plasma concentration-time profile (AUCoo), terminal half-life (t1/2), and fraction of drug excreted unchanged in urine (fe), if available, were obtained or derived from original references, exclusively from IV studies that administered CCB to healthy human volunteers. Several articles focused on drug interactions with grapefruit juice or the impact of renal/hepatic dysfunction, and in such cases, data from the healthy control group were used. Each study was evaluated for study design, PK sampling schedule, bioanalytical and PK analysis methods before inclusion into the final database. The assumption of linear systemic PK was verified by assessing AUCoo versus (IV) dose. Plasma protein binding information was collected from in-vitro experiments to obtain the fraction unbound in plasma (fu). Unbound volume of distribution at a steady state (Vdssu), unbound total (CLtotu), renal (CLrenu), and non-renal clearance (CLnonrenu) were estimated and compared with the relevant physiological references for Vdssu (plasma volume, blood volume, extracellular and intracellular spaces, total body water and body weight) and for the unbound clearances (liver blood flow, renal plasma flow, and glomerular filtration rate, GFR). Final PK property values were obtained by averaging across available studies. The distribution of both PC and PK properties were evaluated, and correlation matrices amongst PC properties were constructed to assess for collinearity. If two PC descriptors were found to be collinear, i.e. r, ≥ 0.8, only one of them was used in the final univariate analysis. Finally, univariate linear regression of all PK variables versus each molecular descriptor was performed; any relationship with p<0.05 and r2≥0.30 was considered to be statistically significant. The PC properties of the final 14 CCB were reasonably normally distributed with few exceptions. Overall, CCBs are small (MW range of 316-496 Da), basic and lipophilic (logD7.4 range of 1.5-5.1) molecules. On the other hand, for the PK properties, the distributions were found to be skewed with high standard deviations. Thus, all PK variables (except fu) were log-transformed. Although CCB are mostly highly plasma protein bound (fu range of 0.2-20%), they are characterized by extensive extravascular tissue distribution (Vdss range of 0.6-20.4 l/kg) and high, mainly metabolic, clearance (CLtot range of 3.7-131.7 ml/min/kg). Clevidipine is the only CCB undergoing extensive, extra-hepatic ester hydrolysis, responsible for the highest CLtot value. Urinary excretion for CCB is negligible. Amlodipine is a PK outlier due to its high Vdss (20.4 l/kg) and low CLtot (6.9 ml/min/kg, due to low hepatic extraction) with fu of 2%. Therefore, the final QSPKR analysis was performed including, as well as excluding amlodipine. Excluding amlodipine, the relationship between fu and logD7.4 was negative and significant (r2 of 0.4, n=12). The relationships between CLtotu, CLnonrenu and CLrenu and logD7.4 were found to be positive and significant (r2 between 0.6-0.7, n=3-12); none of the other PC variables affected any of the clearance terms. Although the relationship between Vdssu and logD7.4 was not significant (r2 of 0.25, n=12), it showed the expected positive slope. In fact, after removing bepridil (the remaining outlier in Vdssu), the relationship with logD7.4 became statistically significant (r2=0.46, n=11). The QSPKR obtained in this study for CCB, with logD7.4 being the main PC determinant for systemic PK properties, were similar to those previously reported for opioids, β-adrenergic receptor ligands and benzodiazepines. However, slope estimates for the relationships of CLnonrenu and CLtotu as a function of logD7.4 for CCB were higher compared to these previously studied compounds, which showed higher sensitivity, most likely as a result of their higher lipophilicity. Overall, lipophilicity measured as logD7.4 was found to be a statistically significant and plausible PC determinant for the biologically relevant systemic PK properties for CCB and other classes of drugs.

The critical conduction mode (CRM) power factor correction converters (PFC) are widely used in industry for low power offline switching mode power supplies. For the CRM PFC, the main advantage is to reduce turn-on loss of the main switch. However, the large inductor current ripple in CRM PFC creates huge DM EMI noise, which requires a big EMI filter. The switching frequency of the CRM PFC is variable in half line cycle which makes the EMI characteristics of the CRM PFC are not clear and have not been carefully investigated. The worst case of the EMI noise, which is the baseline to design the EMI filter, is difficult to be identified. In this paper, an approximate mathematical EMI noise model based on the investigation of the principle of the quasi-peak detection is proposed to predict the DM EMI noise of the CRM PFC. The developed prediction method is verified by measurement results and the predicted DM EMI noise is good to evaluate the EMI performance. Based on the noise prediction, the worst case analysis of the DM EMI noise in the CRM PFC is applied and the worst case can be found at some line and load condition, which will be a great help to the EMI filter design and meanwhile leave an opportunity for the optimization of the whole converter design. What is more, the worst case analysis can be extended to 2-channel interleaved CRM PFC and some interesting characteristics can be observed. For example, the great EMI performance improvement through ripple current cancellation in traditional constant frequency PFC by using interleaving techniques will not directly apply to the CRM PFC due to its variable switching frequency. More research needs to be done to abstract some design criteria for the boost inductor and EMI filter in the interleaved CRM PFC.
Master of Science

The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of this parameter allows spatial diversity at the transmitter along with the receiver to be simulated. The process of going from raw measurement data to discrete arrivals and then to clustered arrivals is analyzed. Many possible errors associated with discrete arrival processing are discussed along with possible solutions. Four clustering methods are compared and their relative strengths and weaknesses are pointed out. The effects that errors in the clustering process have on parameter estimation and model performance are also simulated.

The federal communications commission (FCC) has predicted that, under the current regulatory environment, a spectrum shortage may be faced in the near future. This impending spectrum shortage is in part due to a rapidly increasing demand for wireless services and in part due to inefficient usage of currently licensed bands. A new paradigm pertaining to wireless spectrum allocation, known as cognitive radio (CR), has been proposed as a potential solution to this problem. This dissertation seeks to contribute to research in the field of CR through an investigation into the effect that a primary user (PU) channel occupancy model will have on the performance of a secondary user (SU) in a CR network. The model assumes that PU channel occupancy can be described as a binary process and a two state Hidden Markov Model (HMM) was thus chosen for this investigation. Traditional algorithms for training the model were compared with certain evolutionary-based training algorithms in terms of their resulting prediction accuracy and computational complexity. The performance of this model is important since it provides SUs with a basis for channel switching and future channel allocations. A CR simulation platform was developed and the results gained illustrated the effect that the model had on channel switching and the subsequently achievable performance of a SU operating within a CR network. Performance with regard to achievable SU data throughput, PU disruption rate and SU power consumption, were examined for both theoretical test data as well as data obtained from real world spectrum measurements (taken in Pretoria, South Africa). The results show that a trade-off exists between the achievable SU throughput and the average PU disruption rate. Significant SU performance improvements were observed when prediction modelling was employed and it was found that the performance and complexity of the model were influenced by the algorithm employed to train it. SU performance was also affected by the length of the quick sensing interval employed. Results obtained from measured occupancy data were comparable with those obtained from theoretical occupancy data with an average percentage similarity score of 96% for prediction accuracy (using the Viterbi training algorithm), 90% for SU throughput, 83% for SU power consumption and 71% for PU disruption rate.
Dissertation (MEng)--University of Pretoria, 2012.
Electrical, Electronic and Computer Engineering
unrestricted

The need for reliable, high-throughput, mobile wireless communication technologies has never been greater as increases in the demand for on-the-go access to information, entertainment, and other electronic services continues. Two such technologies, which are at the forefront of current research efforts, are orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) systems, their union being known simply as MIMO-OFDM. The successful performance of these technologies depends upon the availability of accurate information concerning the wireless communication channel. In this dissertation, several issues related to quality of this channel state information (CSI) are studied. Specifically, the first part of this dissertation considers the design of optimal pilot signals for OFDM systems. The optimization is addressed via lower bounds on the estimation error variance, which bounds are given by formulations of the Cram'{e}r-Rao bound (CRB). The second part of this dissertation uses the CRB once again, this time as a tool for evaluating the potential performance of MIMO-OFDM channel estimation and prediction. Bounds are found for several parametric time-varying wideband MIMO-OFDM channel models, and numerical evaluations of these bounds are used to illuminate several interesting features regarding the estimation and prediction of MIMO-OFDM channels. The final part of this dissertation considers the problem of MIMO multiplexing using SVD-based methods when only imperfect CSI is available. For this purpose, general per-MIMO-subchannel signal and interference-plus-noise power expressions are derived to quantify the effects of CSI imperfections, and these expressions are then used to find robust MIMO-SVD power and bit allocations which maintain good overall performance in spite of imperfect CSI.

The thesis is largely built on a collection of published and submitted papers where the main focus is to analyze and optimize single-carrier adaptive coded modulation systems with and without antenna diversity. Multidimensional trellis codes are used as component codes. The majority of the analysis is done with both estimation and prediction errors being incorporated. Both channel estimation and prediction are performed using a pilot-symbol-assisted modulation scheme. Thus, known pilot symbols (overhead information) must be transmitted; which consumes power and also degrades system spectral efficiency. Both power consumption and pilot insertion frequency are optimized such that they are kept at necessary values to maximize system throughput without sacrificing the error rate performance. The results show that efficient and reliable system performance can be achieved over a wide range of the considered average channel quality. Going from a single-input single-output system to both spatially uncorrelated and correlated single-input multiple-ouput (SIMO) systems, and further to an uncorrelated multiple-input multiple-output (MIMO) diversity system, is the evolution of the thesis. In the SIMO case, maximum ratio combining is used to combine the incoming signals, whereas the signals are space-time combined in the MIMO diversity system. The multiple-input single-output system comes out as a special case of a MIMO system. Besides the spatially uncorrelated antenna array, the effect of spatial correlation is also considered in the SIMO case. In this case, only prediction error is considered and channel estimation is assumed to be perfect. At first, the impact of spatial correlation in a predicted system originally designed to operate on uncorrelated channels is quanitifed. Then, a maximum a posteriori (MAP)-optimal “space-time predictor” is derived to take spatial correlation into account. As expected, the results show that the throughput is still lower than the uncorrelated system, but the degradation is decreased when the MAP-optimal space-time predictor is used. Thus, by exploiting the correlation properly, the degradation can be reduced. By numerical examples, we demonstrate the potential effect of limiting the predictor complexity, of fixing the pilot spacing, as well as of assuming perfect estimation. The two first simplifications imply lower system complexity and feedback rate, whereas the last assumption is usually made to ease the mathematical analysis. The numerical examples indicate that all the simplifications can be done without serious impact on the predicted system performance.

The flow characteristics in compound channels with and without vegetation on the floodplain were investigated experimentally and numerically in this thesis. Detailed measurements of velocity and boundary shear stress, using a Pitot tube and an acoustic Doppler velocimeter together with a Preston tube, were undertaken to understand the flow characteristics in compound channels. Eight no-rod cases, two emergent-rod cases and two submerged-rod cases were tested. Unsteady large eddies that occur in the shear layer were explored numerically with Large Eddy Simulation (LES) to identify its generation and its effects on the flow behaviors. Mean flow parameters were predicted using the quasi-2D model by considering the shear effect. Usirgg the data of depth-averaged velocity and boundary shear stress, the contributions of shear-generated turbulence and bed-generated turbulence to the Reynolds shear stress were identified, the apparent shear stress was calculated using the modified method of Shiono and Knight (1991) and the depth-averaged secondary current force was then obtained. Large eddies were important to the lateral momentum exchange in shallow non-vegetated compound channels and even in deep vegetated compound channels. In the compound channel with one-line rods at the floodplain edge, the secondary current forces were of opposite signs in the main channel and on the floodplain and the bed shear stress was smaller than the standard two-dimensional value of yHSo due to the vegetation effect, where y,H,So are the specific weight of water, water depth and bed slope respectively. In vegetated compound channels, the velocity patterns were different to those and the discharges were smaller than those in non-vegetated compound channels under similar relative water depth conditions. The anisotropy of turbulence was the main contribution to the generation of secondary currents in non-vegetated and vegetated compound channels, but the Reynolds stress term was more important in the vegetated compound channels. Results of cross spectra showed the mechanisms of the turbulent shear generation near the main channel-floodplain junction are due to large eddies in the non-vegetated compound channel and owing to wakes in the vegetated compound channel. LES results indicated that large eddies caused significant spatial and temporal fluctuations of velocity and water level in the compound channel and the instantaneousv alues of these flow parameters were significantly higher than the mean values. In vegetated compound channels, the flow moved from the main channel to the floodplain and from the floodplain to the main channel alternately. The characteristic frequencies of the large eddy were less than 1Hz which was consistent with the experimental data. The capability of the quasi-2D model to predict the 2D mean flow parameters in compound channels were assessed under different flow conditions and also improved by using the mean wall velocity as the boundary condition and appropriate values of the lateral gradient of the secondary current force. In the vegetated compound channels, new approaches were proposed to treat the drag force in the cases of oneline emergent rods at the floodplain edge and submerged rods on the floodplain.

Cette thèse a pour but de proposer toutes les avancées possibles dans l’utilisation du modèle de propagation Multi-Resolution Frequency-Domain ParFlow (MR-FDPF). Etant un modèle de propagation radio déterministe, le modèle MR-FDPF possède un haut niveau de précision, mais souffre des limitations communes à tous les modèles déterministes. Par exemple, un canal radio réel n’est pas déterministe, mais un processus aléatoire à cause par exemple des personnes ou objets mobiles, et ne peut donc être décrit fidèlement par un modèle purement déterministe. Dans cette thèse, un modèle semi-déterministe est proposé, basé sur le modèle MR-FDPF, qui introduit une part stochastique pour tenir compte des aspects aléatoires du canal radio réaliste. La partie déterministe du modèle est composée du path loss (atténuation d’espace), et la partie stochastique venant du shadow fading (masquage) et du small scale fading (évanouissement). De même, de nombreux simulateurs de propagation radio ne proposent que la prédiction de la puissance moyenne. Mais pour une simulation précise de la propagation radio il convient de prédire également des informations de fading permettant dès lors une prédiction précise du taux d’erreur binaire (BER) potentiel. Dans cette thèse, l’information de fading est déduite des simulations MR-FDPF et par la suite des valeurs réalistes de BER sont données. Enfin, ces données réalistes de BER permettent d’évaluer l’impact de schémas de modulation adaptatifs. Des résultats sont présentés dans trois configurations : systèmes SISO (mono-antenne à l’émission et à la réception), systèmes à diversité de type MRC, et systèmes large bande de type OFDM
This thesis aims at proposing all the possible enhancements for the Multi-Resolution Frequency-Domain ParFlow (MR-FDPF) model. As a deterministic radio propagation model, the MR-FDPF model possesses the property of a high level of accuracy, but it also suffers from some common limitations of deterministic models. For instance, realistic radio channels are not deterministic but a kind of random processes due to, e.g. moving people or moving objects, thus they can not be completely described by a purely deterministic model. In this thesis, a semi-deterministic model is proposed based on the deterministic MR-FDPF model which introduces a stochastic part to take into account the randomness of realistic radio channels. The deterministic part of the semi-deterministic model is the mean path loss, and the stochastic part comes from the shadow fading and the small scale fading. Besides, many radio propagation simulators provide only the mean power predictions. However, only mean power is not enough to fully describe the behavior of radio channels. It has been shown that fading has also an important impact on the radio system performance. Thus, a fine radio propagation simulator should also be able to provide the fading information, and then an accurate Bit Error Rate (BER) prediction can be achieved. In this thesis, the fading information is extracted based on the MR-FDPF model and then a realistic BER is predicted. Finally, the realistic prediction of the BER allows the implementation of the adaptive modulation scheme. This has been done in the thesis for three systems, the Single-Input Single-Output (SISO) systems, the Maximum Ratio Combining (MRC) diversity systems and the wideband Orthogonal Frequency-Division Multiplexing (OFDM) systems

[ES] Las enfermedades cardiovasculares siguen siendo la principal causa de muerte en Europa. Las arritmias cardíacas son una causa importante de muerte súbita, pero sus mecanismos son complejos. Esto denota la importancia de su estudio y prevención. La investigación sobre electrofisiología cardíaca ha demostrado que las anomalías eléctricas causadas por mutaciones que afectan a canales cardíacos pueden desencadenar arritmias. Sorprendentemente, se ha descubierto una gran variedad de fármacos proarrítmicos, incluidos aquellos que usamos para prevenirlas. Las indicaciones de uso de fármacos actuales intentaron solucionar este problema diseñando una prueba para identificar aquellos fármacos que podían ser peligrosos basado en el bloqueo de un solo canal iónico. El estudio de las interacciones fármaco-canal ha revelado la existencia no sólo de compuestos que bloquean múltiples canales, sino también una gran complejidad en esas interacciones. Esto podría explicar por qué algunos medicamentos pueden mostrar efectos muy diferentes en la misma enfermedad. Existen dos desafíos importantes con respecto a los efectos de los fármacos en la electrofisiología cardíaca. Por un lado, las empresas y entidades reguladoras están buscando una herramienta de alto rendimiento que mejore la detección del potencial proarrítmico durante el desarrollo de fármacos. Por otro lado, los pacientes con anomalías eléctricas a menudo requieren tratamientos personalizados más seguros. Las simulaciones computacionales contienen un poder sin precedentes para abordar fenómenos biofísicos complejos. Deberían ser de utilidad a la hora de determinar las características que definen tanto los efectos beneficiosos como no deseados de los fármacos mediante la reproducción de datos experimentales y clínicos. En esta tesis doctoral, se han utilizado modelos computacionales y simulaciones para dar respuesta a estos dos desafíos. El estudio de los efectos de los fármacos sobre la actividad cardíaca se dividió en el estudio de su seguridad y de su eficacia, respectivamente. Para dar respuesta al primer desafío, se adoptó un enfoque más amplio y se generó un nuevo biomarcador fácil de usar para la clasificación del potencial proarrítmico de los fármacos utilizando modelos del potencial de acción de células y tejidos cardíacos humanos. Se integró el bloqueo de múltiples canales a través de IC50 y el uso de concentraciones terapéuticas con el fin de mejorar el poder predictivo. Luego, se entrenó el biomarcador cuantificando el potencial proarrítmico de 84 fármacos. Los resultados obtenidos sugieren que el biomarcador podría usarse para probar el potencial proarrítmico de nuevos fármacos. Respecto al segundo desafío, se adoptó un enfoque más específico y se buscó mejorar la terapia de pacientes con anomalías eléctricas cardíacas. Por lo tanto, se creó un modelo detallado de la mutación V411M del canal de sodio, causante del síndrome de QT largo, reproduciendo datos clínicos y experimentales. Se evaluaron los posibles efectos beneficiosos de ranolazina, a la par que se aportó información sobre los mecanismos que impulsan la efectividad de la flecainida. Los resultados obtenidos sugieren que, si bien ambos fármacos mostraron diferentes mecanismos de bloqueo de los canales de sodio, un tratamiento con ranolazina podría ser beneficioso en estos pacientes.
[CA] Les malalties cardiovasculars continuen sent la principal causa de mort a Europa. Les arrítmies cardíaques són una causa important de mort sobtada, però els seus mecanismes són complexos. Això denota la importància del seu estudi i prevenció. La investigació sobre electrofisiologia cardíaca ha demostrat que les anomalies elèctriques que afecten a canals cardiacs poden desencadenar arrítmies. Sorprenentment, s'ha descobert una gran varietat de fàrmacs proarrítmics, inclosos aquells que utilitzem per a previndre-les. Les indicacions d'ús de fàrmacs actuals van intentar solucionar aquest problema dissenyant una prova per a identificar aquells fàrmacs que podien ser perillosos basada en el bloqueig d'un sol canal iònic. L'estudi de les interaccions fàrmac-canal ha revelat l'existència no sols de compostos que bloquegen múltiples canals, sinó també una gran complexitat en aquestes interaccions. Això podria explicar per què alguns medicaments poden mostrar efectes molt diferents en la mateixa malaltia. Existeixen dos desafiaments importants respecte als efectes dels fàrmacs en la electrofisiologia cardíaca. D'una banda, les empreses i entitats reguladores estan buscant una eina d'alt rendiment que millore la detecció del potencial proarrítmic durant el desenvolupament de fàrmacs. D'altra banda, els pacients amb anomalies elèctriques sovint requereixen tractaments personalitzats més segurs. Les simulacions computacionals contenen un poder sense precedents per a abordar fenòmens biofísics complexos. Haurien de ser d'utilitat a l'hora de determinar les característiques que defineixen tant els efectes beneficiosos com no desitjats dels fàrmacs mitjançant la reproducció de dades experimentals i clíniques. En aquesta tesi doctoral, s'han utilitzat models computacionals i simulacions per a donar resposta a aquests dos desafiaments. L'estudi dels efectes dels fàrmacs sobre l'activitat cardíaca es va dividir en l'estudi de la seva seguretat i la seva eficacia. Per a donar resposta al primer desafiament, es va adoptar un enfocament més ampli i es va generar un nou biomarcador fàcil d'usar per a la classificació del potencial proarrítmic dels fàrmacs utilitzant models del potencial d'acció de cèl·lules i teixits cardíacs humans. Es va integrar el bloqueig de múltiples canals a través d'IC50 i l'ús de concentracions terapèutiques amb la finalitat de millorar el poder predictiu. Després, es va entrenar el biomarcador quantificant el potencial proarrítmic de 84 fàrmacs. Els resultats obtinguts suggereixen que el biomarcador podria usar-se per a provar el potencial proarrítmic de nous fàrmacs. Respecte al segon desafiament, es va adoptar un enfocament més específic i es va buscar millorar la teràpia de pacients amb anomalies elèctriques cardíaques. Per tant, es va crear un model detallat de la mutació V411M del canal de sodi, causant de la síndrome de QT llarg, reproduint dades clíniques i experimentals. Es van avaluar els possibles efectes beneficiosos de ranolazina, a l'una que es va aportar informació sobre els mecanismes que impulsen l'efectivitat de la flecainida. Els resultats obtinguts suggereixen que, si bé tots dos fàrmacs van mostrar diferents mecanismes de bloqueig dels canals de sodi, un tractament amb ranolazina podria ser beneficiós en aquests pacients.
[EN] Cardiovascular disease remains the main cause of death in Europe. Cardiac arrhythmias are an important cause of sudden death, but their mechanisms are complex. This denotes the importance of their study and prevention. Research on cardiac electrophysiology has shown that electrical abnormalities caused by mutations in cardiac channels can trigger arrhythmias. Surprisingly, a wide variety of drugs have also shown proarrhythmic potential, including those that we use to prevent arrhythmia. Current guidelines designed a test to identify dangerous drugs by assessing their blocking power on a single ion channel to address this situation. Study of drug-channel interactions has revealed not only compounds that block multiple channels but also a great complexity in those interactions. This could explain why similar drugs can show vastly different effects in some diseases. There are two important challenges regarding the effects of drugs on cardiac electrophysiology. On the one hand, companies and regulators are in search of a high throughput tool that improves proarrhythmic potential detection during drug development. On the other hand, patients with electrical abnormalities often require safer personalized treatments owing to their condition. Computer simulations provide an unprecedented power to tackle complex biophysical phenomena. They should prove useful determining the characteristics that define the drugs' beneficial and unwanted effects by reproducing experimental and clinical observations. In this PhD thesis, we used computational models and simulations to address the two abovementioned challenges. We split the study of drug effects on the cardiac activity into the study of their safety and efficacy, respectively. For the former, we took a wider approach and generated a new easy-to-use biomarker for proarrhythmic potential classification using cardiac cell and tissue human action potential models. We integrated multiple channel block through IC50s and therapeutic concentrations to improve its predictive power. Then, we quantified the proarrhythmic potential of 84 drugs to train the biomarker. Our results suggest that it could be used to test the proarrhythmic potential of new drugs. For the second challenge, we took a more specific approach and sought to improve the therapy of patients with cardiac electrical abnormalities. Therefore, we created a detailed model for the long QT syndrome-causing V411M mutation of the sodium channel reproducing clinical and experimental data. We tested the potential benefits of ranolazine, while giving insights into the mechanisms that drive flecainide's effectiveness. Our results suggest that while both drugs showed different mechanisms of sodium channel block, ranolazine could prove beneficial in these patients.
This PhD thesis was developed within the following projects: Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) DPI2015-69125-R (MINECO/FEDER, UE): Simulación computacional para la predicción personalizada de los efectos de los fármacos sobre la actividad cardiaca. Dirección General de Política Científica de la Generalitat Valenciana (PROMETEU2016/088): “Modelos computacionales personalizados multiescala para la optimización del diagnóstico y tratamiento de arritmias cardiacas (personalised digital heart). Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València, Ayuda a Primeros Proyectos de Investigación (PAID-06-18), and by Memorial Nacho Barberá. Instituto de Salud Carlos III (La Fe Biobank PT17/0015/0043).
Cano García, J. (2021). Prediction of the effects of drugs on cardiac activity using computer simulations [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/164094
TESIS

In some species, including humans, red blood cells (RBCs) under low shear stress tend to clump together and form into regular stacks called rouleaux. These stacks are not static, and constantly move and break apart. This phenomenon is referred to as red blood cell aggregation and disaggregation. When modelled as a single liquid, blood behaves as a non-Newtonian fluid. Its viscosity varies, mainly due to the aggregation of RBCs. The aim of this research is to develop a mesoscale computational model for the simulation of RBCs in plasma. This model considers RBC interaction and aggregation to predict blood-flow characteristics such as viscosity, rouleaux size and velocity distribution. In this work, the population-balance modelling (PBM) approach is utilized to model the RBC aggregation process. The PBM approach is a known method that is used for modelling agglomeration and breakage in two-phase flow fluid mechanics to find aggregate size. The PBM model is coupled to the incompressible Navier-Stokes equations for the plasma. Both models are numerically solved simultaneously. The population-balance equation has been used previously in a more restricted form, the Smoluchowski equation, to model blood viscosity, but it has never been fully coupled with the Navier-Stokes equation directly for the numerical modelling of blood flow. This approach results in a comprehensive model which aims to predict RBC aggregate size and their velocities for different flow configurations, as well as their effects on the apparent macro-scale viscosity. The PBM approach does not treat the microscopic physics of aggregation directly but rather uses experimental correlations for aggregation and disaggregation rates to account for the effects of aggregation on the bulk. To find the aggregation rate, a series of experiments on RBC sedimentation due to gravity is designed. In these tests, aggregated RBCs (rouleaux) tend to settle faster than single RBCs and, due to low shear stresses, disaggregation is very low and can be neglected. A high-speed camera is used to acquire video-microscopic pictures of the process. The size of the aggregates and their velocities are extracted using image processing techniques. For image processing, a general Matlab program is developed which can analyze all the images and report the velocity and size distribution of rouleaux. An experimental correlation for disaggregation rate is found using results from a previous steady-state Couette flow experiment. Aggregation and disaggregation rates from these experiments are used to complete the PBM model. Pressure-driven channel flow experiments are then used for the final validation of the model. Comparisons of the apparent viscosity of whole blood in previous experiments show reasonable agreement with the developed model. This model fills a gap between micro-scale and macro-scale treatments and should be more accurate than traditional macro-scale models while being cheaper than direct treatment of RBCs at the micro-scale.

A modelagem computacional tem se tornado uma poderosa ferramenta utilizada mundialmente em pesquisas sobre sistemas de comunicação móvel. Em tais sistemas, a modelagem do canal é fator indispensável, pois as características de mobilidade e propagação presentes nesse tipo de sistema são responsáveis por distorções ocorridas sobre o sinal transmitido. O presente trabalho reúne os principais modelos matemáticos e computacionais de canal de comunicação móvel. Realiza-se uma abordagem histórica sobre o assunto, apresentado a natureza do problema do desvanecimento e a forma como foi modelado inicialmente. Por outro lado, apresentam-se modelos recentes, considerados eficazes do ponto de vista matemático e eficientes do ponto de vista computacional. O trabalho traz como contribuição a proposta de um novo modelo de canal com desvanecimento. Os modelos apresentados foram analisados do ponto de vista matemático por meio de suas propriedades estatísticas. Do ponto de vista numérico e computacional a análise se deu por meio de simulações. A principal conclusão obtida mostra que dois modelos com filtragem no domínio da freqüência, sendo um deles o novo modelo proposto, são os mais indicados para simular formas de onda que representem um canal com desvanecimento Rayleigh. Este trabalho tem a pretensão de ser útil para pesquisadores atuantes na área de modelagem e simulação de sistemas atuais de comunicação móvel.
Computational modelling is a powerful and widely used tool for research in mobile communication systems. In such systems, the communication channel modelling is an indispensable factor, because its mobility and propagation characteristics can cause distortion over the transmitted waveform. This work contains the main mathematical and computing communication channel models. A historical cover is provided, which presents the nature of the problem and the initial modelling of the fading phenomenon. On the other hand, recent models are presented, which are mathematically effective and computationally efficient. One contribution of this work is the proposal of a new fading channel computational model, which was suitably tested and validated. The presented models were mathematically analyzed through its statistical properties. From numerical and computational point of view, the models were analyzed through several simulations. The main conclusion, from analytical and simulated results, shows that two models using frequency filtering are the best choice for the generation of multiple uncorrelated Rayleigh fading waveforms, where one of them is the new proposed model. This work can help mobile communications researchers to suitably model the communication channel in a computer simulation.

This thesis aims at proposing all the possible enhancements for the Multi-Resolution Frequency-Domain ParFlow (MR-FDPF) model. As a deterministic radio propagation model, the MR-FDPF model possesses the property of a high level of accuracy, but it also suffers from some common limitations of deterministic models. For instance, realistic radio channels are not deterministic but a kind of random processes due to, e.g. moving people or moving objects, thus they can not be completely described by a purely deterministic model. In this thesis, a semi-deterministic model is proposed based on the deterministic MR-FDPF model which introduces a stochastic part to take into account the randomness of realistic radio channels. The deterministic part of the semi-deterministic model is the mean path loss, and the stochastic part comes from the shadow fading and the small scale fading. Besides, many radio propagation simulators provide only the mean power predictions. However, only mean power is not enough to fully describe the behavior of radio channels. It has been shown that fading has also an important impact on the radio system performance. Thus, a fine radio propagation simulator should also be able to provide the fading information, and then an accurate Bit Error Rate (BER) prediction can be achieved. In this thesis, the fading information is extracted based on the MR-FDPF model and then a realistic BER is predicted. Finally, the realistic prediction of the BER allows the implementation of the adaptive modulation scheme. This has been done in the thesis for three systems, the Single-Input Single-Output (SISO) systems, the Maximum Ratio Combining (MRC) diversity systems and the wideband Orthogonal Frequency-Division Multiplexing (OFDM) systems.

In telecommunications, distributed cooperative communications refer to techniques which allow different users in a wireless network to share or combine their information in order to increase diversity gain or power gain. Unlike conventional point-to-point communications maximizing the performance of the individual link, distributed cooperative communications enable multiple users to collaborate with each other to achieve an overall improvement in performance, e.g., improved range and data rates. The first part of this dissertation focuses the problem of jointly decoding binary messages from a single distant transmitter to a cooperative receive cluster. The outage probability of distributed reception with binary hard decision exchanges is compared with the outage probability of ideal receive beamforming with unquantized observation exchanges. Low- dimensional analysis and numerical results show, via two simple but surprisingly good approximations, that the outage probability performance of distributed reception with hard decision exchanges is well-predicted by the SNR of ideal receive beamforming after subtracting a hard decision penalty of slightly less than 2 dB. These results, developed in non-asymptotic regimes, are consistent with prior asymptotic results (for a large number of nodes and low per-node SNR) on hard decisions in binary communication systems. We next consider the problem of estimating and tracking channels in a distributed transmission system with multiple transmitters and multiple receivers. In order to track and predict the effective channel between each transmit node and each receive node to facilitate coherent transmission, a linear time-invariant state- space model is developed and is shown to be observable but nonstabilizable. To quantify the steady-state performance of a Kalman filter channel tracker, two methods are developed to efficiently compute the steady-state prediction covariance. An asymptotic analysis is also presented for the homogenous oscillator case for systems with a large number of transmit and receive nodes with closed-form results for all of the elements in the asymptotic prediction covariance as a function of the carrier frequency, oscillator parameters, and channel measurement period. Numeric results confirm the analysis and demonstrate the effect of the oscillator parameters on the ability of the distributed transmission system to achieve coherent transmission. In recent years, the development of efficient radio frequency (RF) radiation wireless power transfer (WPT) systems has become an active research area, motivated by the widespread use of low-power devices that can be charged wirelessly. In this dissertation, we next consider a time division multiple access scenario where a wireless access point transmits to a group of users which harvest the energy and then use this energy to transmit back to the access point. Past approaches have found the optimal time allocation to maximize sum throughput under the assumption that the users must use all of their harvested power in each block of the "harvest-then-transmit" protocol. This dissertation considers optimal time and energy allocation to maximize the sum throughput for the case when the nodes can save energy for later blocks. To maximize the sum throughput over a finite horizon, the initial optimization problem is separated into two sub-problems and finally can be formulated into a standard box- constrained optimization problem, which can be solved efficiently. A tight upper bound is derived by relaxing the energy harvesting causality. A disadvantage of RF-radiation based WPT is that path loss effects can significantly reduce the amount of power received by energy harvesting devices. To overcome this problem, recent investigations have considered the use of distributed transmit beamforming (DTB) in wireless communication systems where two or more individual transmit nodes pool their antenna resources to emulate a virtual antenna array. In order to take the advantages of the DTB in the WPT, in this dissertation, we study the optimization of the feedback rate to maximize the energy efficiency in the WPT system. Since periodic feedback improves the beamforming gain but requires the receivers to expend energy, there is a fundamental tradeoff between the feedback period and the efficiency of the WPT system. We develop a new model to combine WPT and DTB and explicitly account for independent oscillator dynamics and the cost of feedback energy from the receive nodes. We then formulate a "Normalized Weighted Mean Energy Harvesting Rate" (NWMEHR) maximization problem to select the feedback period to maximize the weighted averaged amount of net energy harvested by the receive nodes per unit of time as a function of the oscillator parameters. We develop an explicit method to numerically calculate the globally optimal feedback period.

The data traffic has been growing drastic over the past few years due to digitization and new technologies that are introduced to the market, such as autonomous cars. In order to meet this demand, the MIMO-OFDM system is used in the fifth generation wireless network, 5G. Designing the optimal wireless network is currently the main research within the area of telecommunication. In order to achieve such a system, multiple factors has to be taken into account, such as the suppression of interference from other users. A traditional method called linear minimum mean square error filter is currently used to suppress the interferences. To derive such a filter, a selection of parameters has to be estimated. One of these parameters is the ideal interference plus noise covariance matrix. By gathering prior knowledge of the underlying structure of the interference channel matrices in terms of the number of interferers and their corresponding bandwidths, the estimation of the ideal covariance matrix could be facilitated. As for this thesis, machine learning algorithms were used to extract these prior knowledge. More specifically, a two or three hidden layer feedforward neural network and a support vector machine with a linear kernel was used. The empirical findings implies promising results with accuracies above 95% for each model.
Under de senaste åren har dataanvändningen ökat drastiskt på grund av digitaliseringen och allteftersom nya teknologier introduceras på marknaden, exempelvis självkörande bilar. För att bemöta denna efterfrågan används ett s.k. MIMO-OFDM system i den femte generationens trådlösa nätverk, 5G. Att designa det optimala trådlösa nätverket är för närvarande huvudforskningen inom telekommunikation och för att uppnå ett sådant system måste flera faktorer beaktas, bland annat störningar från andra användare. En traditionell metod som används för att dämpa störningarna kallas för linjära minsta medelkvadratfelsfilter. För att hitta ett sådant filter måste flera olika parametrar estimeras, en av dessa är den ideala störning samt bruskovariansmatrisen. Genom att ta reda på den underliggande strukturen i störningsmatriserna i termer av antal störningar samt deras motsvarande bandbredd, är något som underlättar uppskattningen av den ideala kovariansmatrisen. I följande avhandling har olika maskininlärningsalgoritmer applicerats för att extrahera dessa informationer. Mer specifikt, ett neuralt nätverk med två eller tre gömda lager samt stödvektormaskin med en linjär kärna har använts. De slutliga resultaten är lovande med en noggrannhet på minst 95% för respektive modell.