Dissertations / Theses on the topic 'Adaptive transmit power allocation'
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Tabatabaei, Yazdi Ehsan. "Adaptive Resource Allocation for Wireless Body Sensor Networks." Thesis, University of Canterbury. Computer Science and Software Engineering, 2014. http://hdl.handle.net/10092/9828.
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The IEEE 802.15.4 standard is an interesting technology for use in Wireless Body Sensor Networks (WBSN), where entire networks of sensors are carried by humans. In many environments the sensor nodes experience external interference for example, when the WBSN is operated in the 2.4 GHz ISM band and the human moves in a densely populated city, it will likely experience WiFi interference, with a quickly changing ``interference landscape''. In this thesis we propose Adaptive Resource Allocation schemes, to be carried out by the WBSN, which provided noticeable performance gains in such environments. We investigate a range of adaptation schemes and assess their performance both through simulations and experimentally.
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Karim, Md Anisul. "Weighted layered space-time code with iterative detection and decoding." Thesis, The University of Sydney, 2006. http://hdl.handle.net/2123/1095.
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Multiple antenna systems are an appealing candidate for emerging fourth-generation wireless networks due to its potential to exploit space diversity for increasing conveyed throughput without wasting bandwidth and power resources. Particularly, layered space-time architecture (LST) proposed by Foschini, is a technique to achieve a significant fraction of the theoretical capacity with a reasonable implementation complexity. There has been a great deal of challenges in the detection of space-time signal; especially to design a low-complexity detector, which can efficiently remove multi-layer interference and approach the interference free bound. The application of iterative principle to joint detection and decoding has been a promising approach. It has been shown that, the iterative receiver with parallel interference canceller (PIC) has a low linear complexity and near interference free performance. Furthermore, it is widely accepted that the performance of digital communication systems can be considerably improved once the channel state information (CSI) is used to optimize the transmit signal. In this thesis, the problem of the design of a power allocation strategy in LST architecture to simultaneously optimize coding, diversity and weighting gains is addressed. A more practical scenario is also considered by assuming imperfect CSI at the receiver. The effect of channel estimation errors in LST architecture with an iterative PIC receiver is investigated. It is shown that imperfect channel estimation at an LST receiver results in erroneous decision statistics at the very first iteration and this error propagates to the subsequent iterations, which ultimately leads to severe degradation of the overall performance. We design a transmit power allocation policy to take into account the imperfection in the channel estimation process. The transmit power of various layers is optimized through minimization of the average bit error rate (BER) of the LST architecture with a low complexity iterative PIC detector. At the receiver, the PIC detector performs both interference regeneration and cancellation simultaneously for all layers. A convolutional code is used as the constituent code. The iterative decoding principle is applied to pass the a posteriori probability estimates between the detector and decoders. The decoder is based on the maximum a posteriori (MAP) algorithms. A closed-form optimal solution for power allocation in terms of the minimum BER is obtained. In order to validate the effectiveness of the proposed schemes, substantial simulation results are provided.
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Karim, Md Anisul. "Weighted layered space-time code with iterative detection and decoding." School of Electrical & Information Engineering, 2006. http://hdl.handle.net/2123/1095.
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Master of Engineering (Research)Multiple antenna systems are an appealing candidate for emerging fourth-generation wireless networks due to its potential to exploit space diversity for increasing conveyed throughput without wasting bandwidth and power resources. Particularly, layered space-time architecture (LST) proposed by Foschini, is a technique to achieve a significant fraction of the theoretical capacity with a reasonable implementation complexity. There has been a great deal of challenges in the detection of space-time signal; especially to design a low-complexity detector, which can efficiently remove multi-layer interference and approach the interference free bound. The application of iterative principle to joint detection and decoding has been a promising approach. It has been shown that, the iterative receiver with parallel interference canceller (PIC) has a low linear complexity and near interference free performance. Furthermore, it is widely accepted that the performance of digital communication systems can be considerably improved once the channel state information (CSI) is used to optimize the transmit signal. In this thesis, the problem of the design of a power allocation strategy in LST architecture to simultaneously optimize coding, diversity and weighting gains is addressed. A more practical scenario is also considered by assuming imperfect CSI at the receiver. The effect of channel estimation errors in LST architecture with an iterative PIC receiver is investigated. It is shown that imperfect channel estimation at an LST receiver results in erroneous decision statistics at the very first iteration and this error propagates to the subsequent iterations, which ultimately leads to severe degradation of the overall performance. We design a transmit power allocation policy to take into account the imperfection in the channel estimation process. The transmit power of various layers is optimized through minimization of the average bit error rate (BER) of the LST architecture with a low complexity iterative PIC detector. At the receiver, the PIC detector performs both interference regeneration and cancellation simultaneously for all layers. A convolutional code is used as the constituent code. The iterative decoding principle is applied to pass the a posteriori probability estimates between the detector and decoders. The decoder is based on the maximum a posteriori (MAP) algorithms. A closed-form optimal solution for power allocation in terms of the minimum BER is obtained. In order to validate the effectiveness of the proposed schemes, substantial simulation results are provided.
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Shi, Zhengyan 1975. "Transmit antenna selected spatial multiplexing systems with power allocation." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99538.
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Vertical Bell Lab Layered Space-Time (VBLAST) is an emerging spatial modulation technique, that provides high spectral efficiency due to its use of multiple transmit and receiver antennas. We present novel schemes; consisting of combinations of Transmit Antenna Selection (TAS) with Power Allocation (PA), to improve the error rate performance of VBLAST systems. Our schemes provide significant performance gain over VLAST because of enhanced transmit diversity introduced by transmit antenna selection. Our scheme may be used for uplink wireless system, where the total power is limited by the mobile terminal battery. The effect of limited rate feedback link is investigated by sending quantized power weights from receiver to transmitter. The simulation results show that even one-bit, codebook for power weights can achieve performance close to that of unlimited rate feedback link in low and medium SNR regions. We also present a novel PA technique alloting power in the joint space-frequency domain to reduce the error rate, and apply our scheme to frequency selective MIMO-OFDM channels. In addition, an analytical analysis of transmit correlated Successive interference Cancelling Zero Forcing (SIC-ZF) VBLAST in flat fading channels is presented. Over frequency selective channels, the performance of SIC-ZF VBLAST is assessed by computer simulation.
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Chung, Jong-Sun. "Fast Power Allocation Algorithms for Adaptive MIMO Systems." Thesis, University of Canterbury. Electrical and Computer Engineering, 2009. http://hdl.handle.net/10092/3764.
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Recent research results have shown that the MIMO wireless communication architecture is a promising approach to achieve high bandwidth efficiencies.
MIMO wireless channels can be simply defined as a link for which both the
transmitting and receiving ends are equipped with multiple antenna elements.
Adaptive modulation and power allocation could be used to further improve the performance of MIMO systems.
This thesis focuses on developing a fast and high performance power allocation algorithm. Three power allocation algorithms are proposed in this thesis and their performances are compared in various system sizes and transceiver architectures. Among the three algorithms proposed in this thesis, the fast algorithm may be considered as the best power allocation algorithm since the performance of the fast algorithm is almost as good as the fullsearch (optimal)algorithm and the mean processing time is considerably less than the fullsearch algorithm. The fast algorithm achieves about 97.6% agreement with the optimal throughput on average. In addition, the time taken to find the power scaling factors using the fullsearch algorithm is about 2300 times longer than the processing time of the fast algorithm in a 6 x 6 system when the SNR is 20dB.
As an extension to the power allocation process, excess power allocation methods are introduced. Excess power is the unused power during the power
allocation process. The power allocation algorithm allocates power to each received SNR to maximize the throughput of the system whereas the excesspower allocation distributes the excess power to each SNR to improve both the instantaneous and temporal behavior of the system. Five different excess power allocation methods are proposed in this thesis. These methods were simulated in the Rayleigh fading channel with different Doppler frequencies, fD = 10Hz,50Hz and 100Hz, where the ACF of the channel coefficients are given by the Jakes' model. The equal BER improvement method showed a slightly better performance than the other methods. The equal BER improvement method enables the system to maintain the power scaling factors without sacrificing QoS for 19.6 ms on average when the maximum Doppler shift is 10Hz.
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Berggren, Fredrik. "Power control and adaptive resource allocation in DS-CDMA systems." Doctoral thesis, KTH, Signals, Sensors and Systems, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3568.
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Ahmed, Safayet N. "Adaptive CPU-budget allocation for soft-real-time applications." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52215.
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The focus of this dissertation is adaptive CPU-budget allocation for periodic soft-real-time applications. The presented algorithms are developed in the context of a power-management framework.
First, the prediction-based bandwidth scheduler (PBS) is developed. This algorithm is designed to adapt CPU-budget allocations at a faster rate than previous adaptive algorithms. Simulation results are presented to demonstrate that this approach allows for a faster response to under allocations than previous algorithms. A second algorithm is presented called Two-Stage Prediction (TSP) that improves on the PBS algorithm. Specifically, a more sophisticated algorithm is used to predict execution times and a stronger guarantee is provided on the timeliness of jobs. Implementation details and experimental results are presented for both the PBS and TSP algorithms.
An abstraction is presented called virtual instruction count (VIC) to allow for more efficient budget allocation in power-managed systems. Power management decisions affect job-execution times. VIC is an abstract measure of computation that allows budget allocations to be made independent of power-management decisions. Implementation details and experimental results are presented for a VIC-based budget mechanism.
Finally, a power-management framework is presented called the linear adaptive models based system (LAMbS). LAMbS is designed to minimize power consumption while honoring budget allocations specified in terms of VIC.
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Cardieri, Paulo. "Resource Allocation and Adaptive Antennas in Cellular Communications." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/29051.
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The rapid growth in demand for cellular mobile communications and emerging fixed wireless access has created the need to increase system capacity through more efficient utilization of the frequency spectrum, and the need for better grade of service. In cellular systems, capacity improvement can be achieved by reducing co-channel interference.
Several techniques have been proposed in literature for mitigating co-channel interference, such as adaptive antennas and power control. Also, by allocating transmitter power and communication channels efficiently (resource allocation), overall co-channel interference can be maintained below a desired maximum tolerable level, while maximizing the carried traffic of the system.
This dissertation presents investigation results on the performance of base station adaptive antennas, power control and channel allocation, as techniques for capacity improvement. Several approaches are analyzed. Firstly, we study the combined use of adaptive antennas and fractional loading factor, in order to estimate the potential capacity improvement achieved by adaptive antennas.
Next, an extensive simulation analysis of a cellular network is carried out aiming to investigate the complex interrelationship between power control, channel allocation and adaptive antennas. In the first part of this simulation analysis, the combined use of adaptive antennas, power control and reduced cluster size is analyzed in a cellular system using fixed channel allocation.
In the second part, we analyze the benefits of combining adaptive antennas, dynamic channel allocation and power control. Two representative channel allocation algorithms are considered and analyzed regarding how efficiently they transform reduced co-channel interference into higher carried traffic. Finally, the spatial filtering capability of adaptive antennas is used to allow several users to share the same channel within the same cell. Several allocation algorithms combined with power control are analyzed.Ph. D.
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Liu, Feng. "Lifetime maximization through adaptive power allocation in reconfigurable system design for wireless systems /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?ECED%202009%20LIU.
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Alam, Muhammad Mahtab. "Power-Aware adaptive techniques for wireless sensor networks." Thesis, Rennes 1, 2013. http://www.theses.fr/2013REN1S049/document.
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Les Réseaux de capteurs sans fil (WSN) sont une technologie émergente avec des applications potentielles dans divers domaines de la vie quotidienne, tels que la surveillance structurelle et environnementale, la médecine, la surveillance militaire, les explorations robotisées, etc. Les nœuds de capteurs doivent fonctionner pendant une longue période avec des batteries capacité limitée, par conséquent le facteur plus important dans les WSN est la consommation d'énergie. Dans cette thèse, nous proposons des techniques d'optimisation algorithmiques dynamiques, et adaptative pour la réduction de l'énergie. Tout d'abord, un modèle énergétique précis est présenté. Ce modèle repose sur des mesures réelles de courant consommé pour différents scénarios qui peuvent se produire lors de la communication entre les nœud. Il en est conclu que la couche MAC joue un rôle essentiel dans la réduction de l'énergie consommée. Ensuite, un protocole MAC dynamique est présenté. Il adapte de manière dynamique l’intervalle de réveil des nœuds de capteurs à partir d’une estimation du trafic. L’algorithme adaptatif modélisé de façon heuristique pour comprendre le comportement de convergence des paramètres algorithmiques. Le protocole est appliqué sur des réseaux de capteurs corporels et il surclasse les autres protocoles MAC en termes de latence ainsi que de consommation d'énergie ce qui permet donc d'augmenter la durée de vie de trois à six fois. Enfin, une technique basée sur l’optimisation adaptative de la puissance d'émission radio est appliquée sur des canaux variant dans le temps. La puissance de sortie est réglée dynamiquement au meilleur niveau de puissance selon l’état du canal, ce qui diminue la consommation d’un facteur deuxWireless Sensor Networks (WSN) are a fast emerging technology with potential applications in various domains of daily-life, such as structural and environmental monitoring, medicine, military surveillance, robotic explorations etc. WSN devices are required to operate for a long time with limited battery capacity, therefore, the most important constraint in WSN is energy consumption. In this thesis, we propose algorithmic-level dynamic and adaptive optimization techniques for energy reduction in WSN. First, an accurate energy model is presented. This model relies on real-time power measurements of various scenarios that can occur during communication between sensor nodes. It is concluded that MAC layer plays a pivotal role for energy reduction. Then, a traffic-aware dynamic MAC protocol is presented which dynamically adapts the wake-up schedule of sensor nodes through traffic estimation. An adaptive algorithm is designed for this purpose that is heuristically modeled to understand the convergence behavior of algorithmic parameters. The proposed protocol is applied to body area networks and it outperforms other low-power MAC protocols in terms of latency as well as energy consumption and consequently increases the lifetime from three to six times. Finally, an SNR-based adaptive transmit power optimization technique is applied under time-varying channels. The output power is dynamically tuned to best power level under slow varying channel, which results in an average gain by two times
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LI, XUAN. "Response Adaptive Designs in the Presence of Mismeasurement." Elsevier, 2012. http://hdl.handle.net/1993/8095.
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Response adaptive randomization represents a major advance in clinical trial methodology that helps balance the benefits of the collective and the benefits of the individual and improves efficiency without undermining the validity and integrity of the clinical research. Response adaptive designs use information so far accumulated from the trial to modify the randomization procedure and deliberately bias treatment allocation in order to assign more patients to the potentially better treatment. No attention has been paid to incorporating the problem of errors-in-variables in adaptive clinical trials. In this work, some important issues and methods of response adaptive design of clinical trials in the presence of mismeasurement are examined. We formulate response adaptive designs when the dichotomous response may be misclassified. We consider the optimal allocations under various objectives, investigate the asymptotically best response adaptive randomization procedure, and discuss effects of misclassification on the optimal allocation. We derive explicit expressions for the variance-penalized criterion with misclassified binary responses and propose a new target proportion of treatment allocation under the criterion. A real-life clinical trial and some related simulation results are also presented.
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Huang, Jinliang. "Adaptive MIMO Systems with Channel State Information at Transmitter." Doctoral thesis, KTH, Kommunikationssystem, CoS, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9777.
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This dissertation presents adaptation techniques that can achieve high spectral efficiency for single user multiple-input multiple-output (MIMO) systems. Two types of adaptation techniques, adaptive modulation and adaptive powe allocation, are employed to adapt the rate and the transmit power to fading channels. We start by investigating the adaptive modulation subject to a certain bit-error-ratio (BER) constraint, either instantaneous BER constraint or average BER constraint. The resulting average spectral efficiencies are obtained in closed-form expressions. It turns out that, by employing the average BER constraint, we can achieve the optimal average spectra efficiency at the cost of prohibitive computational complexity. On the other hand, instantaneous BER constraint leads to inferior performance with little computational complexity. In order to achieve comparable performance to the average BER constraint with limited complexity, a non-linear optimization method is proposed. To further enhance the average spectra efficiency, adaptive power allocation schemes are considered to adjust the transmit power across the temporal domain or the spatial domain, depending on the specific situation. Provided the closed-form expressions of the average spectral efficiency, the optimal MIMO coding scheme that offers the highest average spectral efficiency under the same circumstances can be identified. As we take into account the effect of imperfect channel estimation, the adaptation techniques are revised to tolerate interference introduced by the channel estimation errors. As a result, the degradation with respect to the average spectral efficiency is in proportion to signal-to-noise ratio (SNR). In order to facilitate fast development and verification of the adaptation schemes proposed for various MIMO systems, a reconfigurable Link Layer Simulator (LiLaS) which accommodates a variety of wireless/wireline applications is designed in the environment of MATLAB/OCTAVE. The idea of the simulator is originated from Software Defined Radio (SDR) and evolved to suit Cognitive Radio (CR) applications. For the convenience of modification and reconfiguration, LiLaS is functionally divided into generic blocks and all blocks are parameterized.QC 20100812
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Huang, Jinliang. "Adaptation in multiple input multiple output systems with channel state information at transmitter." Licentiate thesis, Stockholm : Institutionen för elektronik, dator- och programvarusystem, Kungliga tekniska högskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4443.
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Hussain, Nasir. "Cooperative communication in relay assisted wireless access networks." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/103528/1/Nasir_Hussain_Thesis.pdf.
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This research investigates the benefits of user cooperation in wireless communications systems. The dynamics of wireless cooperative communication systems are studied by a comprehensive study of two essential characteristics of cooperation, optimal relay selection criteria and practical channel estimation. A novel relay selection model based on realistic channel estimation is proposed and analysed. Furthermore, the gains are experimentally evaluated using a wireless communication testbed. The outcomes of this research reveal that incorporating cooperative techniques with an adaptive relay selection strategy into existing wireless communication can significantly reduce the required power and the impact of wireless channel impairments.
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Dang, Hieu. "Adaptive multiobjective memetic optimization: algorithms and applications." Journal of Cognitive Informatics and Natural Intelligence, 2012. http://hdl.handle.net/1993/30856.
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The thesis presents research on multiobjective optimization based on memetic computing and its applications in engineering. We have introduced a framework for adaptive multiobjective memetic optimization algorithms (AMMOA) with an information theoretic criterion for guiding the selection, clustering, and local refinements. A robust stopping criterion for AMMOA has also been introduced to solve non-linear and large-scale optimization problems. The framework has been implemented for different benchmark test problems with remarkable results.
This thesis also presents two applications of these algorithms. First, an optimal image data hiding technique has been formulated as a multiobjective optimization problem with conflicting objectives. In particular, trade-off factors in designing an optimal image data hiding are investigated to maximize the quality of watermarked images and the robustness of watermark. With the fixed size of a logo watermark, there is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. We propose to use a hybrid between general regression neural networks (GRNN) and the adaptive multiobjective memetic optimization algorithm (AMMOA) to solve this challenging problem. This novel image data hiding approach has been implemented for many different test natural images with remarkable robustness and transparency of the embedded logo watermark. We also introduce a perceptual measure based on the relative Rényi information spectrum to evaluate the quality of watermarked images.
The second application is the problem of joint spectrum sensing and power control optimization for a multichannel, multiple-user cognitive radio network. We investigated trade-off factors in designing efficient spectrum sensing techniques to maximize the throughput and minimize the interference. To maximize the throughput of secondary users and minimize the interference to primary users, we propose a joint determination of the sensing and transmission parameters of the secondary users, such as sensing times, decision threshold vectors, and power allocation vectors. There is a conflict between these two objectives, thus a multiobjective optimization problem is used again in the form of AMMOA. This algorithm learns to find optimal spectrum sensing times, decision threshold vectors, and power allocation vectors to maximize the averaged opportunistic throughput and minimize the averaged interference to the cognitive radio network.February 2016
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BAIG, CLEMENT RANJITH ANTHIKKAD & IRFAN AHMED. "PERFORMANCE ENHANCEMENT OF OFDM IN PAPR REDUCTION USING NEW COMPANDING TRANSFORM AND ADAPTIVE AC EXTENSION ALGORITHM FOR NEXT GENERATION NETWORKSPERFORMANCE ENHANCEMENT OF OFDM IN PAPR REDUCTION USING NEW COMPANDING TRANSFORM AND ADAPTIVE AC EXTENSION ALGORITHM FOR NEXT GENERATION NETWORKS." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-6011.
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This paper presents a new hybrid PAPR reduction technique for the OFDM signal, which combines a multiple symbol representations method with a signal clipping method. The clipping method is a nonlinear PAPR reduction scheme, where the amplitude of the signal is limited to a given threshold. Considering the fact that the signal must be interpolated before A/D conversion, a variety of clipping methods has been proposed. Some methods suggest the clipping before interpolation, having the disadvantage of the peaks re-growth. Other methods contributed that the clipping after interpolation, having the disadvantage of out-of-band power production. In order to overcome this problem different filtering techniques have been proposed. Filtering can also cause peak re-growth, but less than the clipping before interpolation. Another clipping technique supposes that only subcarriers having the highest phase difference between the original signal and its clipped variant will be changed. This is the case of the partial clipping method. To further reduce the PAPR, the dynamic of the clipped signal can be compressed. Linear methods like partial transmit sequence or selective mapping has been proposed for the reduction of PAPR as well. Another PAPR reduction method is the tone reservation. It uses tones on which no data is sent to reduce the transmitted signal peaks. Derivatives of this method with lower computation complexity and improved performance have been proposed: One-Tone One-Peak and one by-one iteration. A similar PAPR reduction method is the multiple symbol representations, where alternative signalling points are used to represent one symbol. The simulation results highlight the advantages of the proposed PAPR reduction method.The proposed technique namely Adaptive Active Constellation Extension (Adaptive ACE) Algorithm reduced the high Peak-to-Average Power Ratio (PAPR) of the Orthogonal Frequency Division Multiplexing (OFDM) systems. The Peak-to-Average Power Ratio (PAPR) is equal to 6.8 dB for the target clipping ratios of 4 dB, 2 dB and 0 dB by using Adaptive Active Constellation Extension (Adaptive ACE) Algorithm. Thus, the minimum PAPR can be achieved for low target clipping ratios. The Signal-to-Noise Ratio (SNR) of the Orthogonal Frequency Division Multiplexing (OFDM) signal obtained by the Adaptive Active Constellation Extension (Adaptive ACE) algorithm is equal to 1.2 dB at a Bit Error Rate (BER) of 10-0..4 for different constellation orders like 4-Quadrature Amplitude Modulation (4-QAM), 16-Quadrature Amplitude Modulation (16-QAM) and 64-Quadrature Amplitude Modulation (16-QAM). Here, the Bit Error Rate of 10-0.4 or 0.398, that means a total of 398-bits are in error when 1000-bits are transmitted via a communication channel or approximately 4-bits are in error when 10-bits are transmitted via a communication channel, which is high when compared to that of the original Orthogonal Frequency Division Multiplexing (OFDM) signal. The other problems faced by the Adaptive Active Constellation Extension (Adaptive ACE) algorithm are Out-of-Band Interference (OBI) and peak regrowth. Here, the Out-of-Band Interference (OBI) is a form of noise or an unwanted signal, which is caused when the original Orthogonal Frequency Division Multiplexing (OFDM) signal is clipped for reducing the peak signals which are outside of the predetermined area and the peak regrowth is obtained after filtering the clipped signal. The peak regrowth results to, increase in the computational time and computational complexity. In this paper, we have proposed a PAPR reduction scheme to improve the bit error rate performance by applying companding transform technique. Hence, 1-1.5 dB reduction in PAPR with this Non-companding technique is achieved. In Future, We can accept to implement the same on Rician and Rayleigh channels.
Clement Ranjith Anthikkad (E-mail: clement.ranjith@gmail.com / clan11@bth.se) & Irfan Ahmed Baig (E-mail: baig.irfanahmed@gmail.com / ir-a11@bth.se )
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Liu, Xinyi. "Contribution to adaptative sliding mode, fault tolerant control and control allocation of wind turbine system." Thesis, Belfort-Montbéliard, 2016. http://www.theses.fr/2016BELF0295/document.
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Les principaux défis pour le déploiement de systèmes de conversion de l'énergie éolienne est de maximiser la puissance électrique produite, malgré les variations des conditions météorologiques, tout en minimisant les coûts de fabrication et de maintenance du système. L'efficacité de la turbine éolienne est fortement dépendante des perturbations de l'environnement et des paramètres variables du système, tels que la vitesse du vent et l'angle de tangage. Les incertitudes sur le système sont difficiles à modéliser avec précision alors qu'ils affectent sa stabilité.Afin d'assurer un état de fonctionnement optimal, malgré les perturbations, le commande adaptative peut jouer un rôle déterminant. D'autre part, la synthèse de commandes tolérantes aux défauts, capables de maintenir les éoliennes connectées au réseau après la survenance de certains défauts est indispensable pour le bon fonctionnement du réseau. Le travail de cette thèse porte sur la mise en place de lois de commande adaptatives et tolérantes aux défauts appliqués aux systèmes de conversion de l'énergie éolienne. Après un état de l'art, les contributions de la thèse sont :Dans la première partie de la thèse, un modèle incertain non linéaire du système de conversion d'énergie éolienne avec un générateur à induction à double alimentation est proposé. Une nouvelles approches de commande adaptative par mode glissant est synthétisée et ensuite appliquée pour optimiser l'énergie issue de l'éolienne.Dans la deuxième partie, une nouvelle commande par modes glissants tolérante aux défauts et basée sur les modes glissants intégrales est présentée. Puis, cette méthode est appliquée afin de forcer la vitesse de la turbine éolienne à sa valeur optimale en prenant en compte des défauts qui surviennent sur l'actionneurThe main challenges for the deployment of wind energy conversion systems (WECS) are to maximize the amount of good quality electrical power extracted from wind energy over a significantly wide range of weather conditions and minimize both manufacturing and maintenance costs. Wind turbine's efficiency is highly dependent on environmental disturbances and varying parameters for operating conditions, such as wind speed, pitch angle, tip-speed ratio, sensitive resistor and inductance. Uncertainties on the system are hard to model exactly while it affects the stability of the system. In order to ensure an optimal operating condition, with unknown perturbations, adaptive control can play an important role. On the other hand, a Fault Tolerant Control (FTC) with control allocation that is able to maintain the WECS connected after the occurrence of certain faults can avoid major economic losses. The thesis work concerns the establishment of an adaptive control and fault diagnosis and tolerant control of WECS. After a literature review, the contributions of the thesis are:In the first part of the thesis, a nonlinear uncertain model of the wind energy conversion system with a doubly fed induction generator (DFIG) is proposed. A novel Lyapunov-based adaptive Sliding Mode (HOSM) controller is designed to optimize the generated power.In the second part, a new output integral sliding mode methodology for fault tolerant control with control allocation of linear time varying systems is presented. Then, this methodology has been applied in order to force the wind turbine speed to its optimal value the presence of faults in the actuator
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Yu, Yi. "Radio Resource Planning in Low Power Wide Area IoT Networks." Electronic Thesis or Diss., Paris, CNAM, 2021. http://www.theses.fr/2021CNAM1287.
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Cette thèse étudie le problème de planification des ressources pour les réseaux IoT longues portées basés sur les technologies NB-IoT et LoRa. Dans les deux cas, on suppose que les capteurs et les collecteurs sont distribués suivant des processus de points de Poisson spatial indépendants marqués par le caractère aléatoire du canal. Pour le NB-IoT, nous élaborons un modèle de dimensionnement statistique qui estime le nombre de ressources radio nécessaires en fonction du délai d’accès toléré, de la densité des nœuds actifs, des collecteurs et de la configuration de l’antenne. Pour le réseau LoRa, nous proposons une technique d’allocation de plusieurs sous-bandes pour atténuer le niveau élevé d’interférence induit par les nœuds qui transmettent avec le même facteur d’étalement. Pour allouer dynamiquement le facteur d’étalement et la puissance, nous présentons une approche d’apprentissage automatique avec multi-agents qui permet d’améliorer l’efficacité énergétiqueIn this thesis, we focus on radio resource planning issues for low power wide area networks based on NB-IoT and LoRa technologies. In both cases, the average behavior of the network is considered by assuming the sensors and the collectors are distributed according to independent random Poisson Point Process marked by the channel randomness. For the NB-IoT, we elaborate a statistical dimensioning model that estimates the number of radio resources in the network depending on the tolerated delay access, the density of active nodes, the collectors, and the antenna configuration with single and multi-user transmission. For the LoRa network, we propose a multi-sub band allocation technique to mitigate the high level of interference induced by nodes that transmit with the same spreading factor. To dynamically allocate the spreading factor and the power, we present a Q-learning multi-agent approach to improve the energy efficiency
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Nikbakht, Silab Rasoul. "Unsupervised learning for parametric optimization in wireless networks." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/671246.
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This thesis studies parametric optimization in cellular and cell-free networks, exploring data-based and expert-based paradigms. Power allocation and power control, which adjust the transmit power to meet different fairness criteria such as max-min or max-product, are crucial tasks in wireless communications that fall into the parametric optimization category. The state-of-the-art approaches for power control and power allocation often demand huge computational costs and are not suitable for real-time applications. To address this issue, we develop a general-purpose unsupervised-learning approach for solving parametric optimizations; and extend the well-known fractional power control algorithm.
In the data-based paradigm, we create an unsupervised learning framework that defines a custom neural network (NN), incorporating expert knowledge to the NN loss function to solve the power control and power allocation problems. In this approach, a feedforward NN is trained by repeatedly sampling the parameter space, but, rather than solving the associated optimization problem completely, a single step is taken along the gradient of the objective function. The resulting method is applicable for both convex and non-convex optimization problems. It offers two-to-three orders of magnitude speedup in the power control and power allocation problems compared to a convex solver—whenever appliable.
In the expert-driven paradigm, we investigate the extension of fractional power control to cell-free networks. The resulting closed-form solution can be evaluated for uplink and downlink effortlessly and reaches an (almost) optimum solution in the uplink case.
In both paradigms, we place a particular focus on large scale gains—the amount of attenuation experienced by the local-average received power. The slow-varying nature of the large-scale gains relaxes the need for a frequent update of the solutions in both the data-driven and expert-driven paradigms, enabling real-time application for both methods.Aqueta tesis estudia l’optimització paramètrica a les xarxes cel.lulars i xarxes cell-free, explotant els paradigmes basats en dades i basats en experts. L’assignació i control de la potencia, que ajusten la potencia de transmissió per complir amb diferents criteris d’equitat com max-min o max-product, son tasques crucials en les telecomunicacions inalàmbriques pertanyents a la categoria d’optimització paramètrica. Les tècniques d’última generació per al control i assignació de la potència solen exigir enormes costos computacionals i no son adequats per aplicacions en temps real. Per abordar aquesta qüestió, desenvolupem una tècnica de propòsit general utilitzant aprenentatge no supervisat per resoldre optimitzacions paramètriques; i al mateix temps ampliem el reconegut algoritme de control de potencia fraccionada. En el paradigma basat en dades, creem un marc d’aprenentatge no supervisat que defineix una xarxa neuronal (NN, sigles de Neural Network en Anglès) especifica, incorporant coneixements experts a la funció de cost de la NN per resoldre els problemes de control i assignació de potència. Dins d’aquest enfocament, s’entrena una NN de tipus feedforward mitjançant el mostreig repetit en l’espai de paràmetres, però, en lloc de resoldre completament el problema d’optimització associat, es pren un sol pas en la direcció del gradient de la funció objectiu. El mètode resultant ´es aplicable tant als problemes d’optimització convexos com no convexos. Això ofereix una acceleració de dos a tres ordres de magnitud en els problemes de control i assignació de potencia en comparació amb un algoritme de resolució convexa—sempre que sigui aplicable. En el paradigma dirigit per experts, investiguem l’extensió del control de potencia fraccionada a les xarxes sense cèl·lules. La solució tancada resultant pot ser avaluada per a l’enllaç de pujada i el de baixada sense esforç i assoleix una solució (gaire) òptima en el cas de l’enllaç de pujada. En ambdós paradigmes, ens centrem especialment en els guanys a gran escala—la quantitat d’atenuació que experimenta la potencia mitja local rebuda. La naturalesa de variació lenta dels guanys a gran escala relaxa la necessitat d’una actualització freqüent de les solucions tant en el paradigma basat en dades com en el basat en experts, permetent d’aquesta manera l’ús dels dos mètodes en aplicacions en temps real.
Esta tesis estudia la optimización paramétrica en las redes celulares y redes cell-free, explorando los paradigmas basados en datos y en expertos. La asignación y el control de la potencia, que ajustan la potencia de transmisión para cumplir con diferentes criterios de equidad como max-min o max-product, son tareas cruciales en las comunicaciones inalámbricas pertenecientes a la categoría de optimización paramétrica. Los enfoques más modernos de control y asignación de la potencia suelen exigir enormes costes computacionales y no son adecuados para aplicaciones en tiempo real. Para abordar esta cuestión, desarrollamos un enfoque de aprendizaje no supervisado de propósito general que resuelve las optimizaciones paramétricas y a su vez ampliamos el reconocido algoritmo de control de potencia fraccionada. En el paradigma basado en datos, creamos un marco de aprendizaje no supervisado que define una red neuronal (NN, por sus siglas en inglés) específica, incorporando conocimiento de expertos a la función de coste de la NN para resolver los problemas de control y asignación de potencia. Dentro de este enfoque, se entrena una NN de tipo feedforward mediante el muestreo repetido del espacio de parámetros, pero, en lugar de resolver completamente el problema de optimización asociado, se toma un solo paso en la dirección del gradiente de la función objetivo. El método resultante es aplicable tanto a los problemas de optimización convexos como no convexos. Ofrece una aceleración de dos a tres órdenes de magnitud en los problemas de control y asignación de potencia, en comparación con un algoritmo de resolución convexo—siempre que sea aplicable. Dentro del paradigma dirigido por expertos, investigamos la extensión del control de potencia fraccionada a las redes cell-free. La solución de forma cerrada resultante puede ser evaluada para el enlace uplink y el downlink sin esfuerzo y alcanza una solución (casi) óptima en el caso del enlace uplink. En ambos paradigmas, nos centramos especialmente en las large-scale gains— la cantidad de atenuación que experimenta la potencia media local recibida. La naturaleza lenta y variable de las ganancias a gran escala relaja la necesidad de una actualización frecuente de las soluciones tanto en el paradigma basado en datos como en el basado en expertos, permitiendo el uso de ambos métodos en aplicaciones en tiempo real.
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溫振鵬. "Achieving Fair Rate by Transmit Power Allocation for Underdetermined MIMO Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/71919130549218844541.
Full textAbstract:
碩士國立交通大學
電信工程研究所
98
In wireless communication systems, multiple-input multiple-output (MIMO) technology offers significant increases in data rate and link range without additional bandwidth and transmit power. However, in uplink multi-user MIMO systems, some users will suffer from small channel gains due to being far away from the base station or blocked by obstacles in practical environments. This result in poor data rates for those users. In this thesis, we propose a transmit power allocation scheme with fair rate allocation for all users. We reformulate a nonlinear optimization problem to a modified form which can be applied to the existing algorithms. The proposed fairness scheme also leads to uniform sub-channel gains. Thus the equivalent channel matrix will tend to be well-conditioned. Since efficient decoders of underdetermined MIMO systems are based on sphere decoders, the decoding complexity can be reduced with a smaller channel condition number. Finally, we also propose an alternative utility function to improve the condition number, to further reduce the decoding complexity. Simulation results confirm the effectiveness of the proposed methods.
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Rezk, Mhd Dherar. "Improved layered space-time architecture with unequal transmit power allocation and multi-stage decoding." Thesis, 2006. http://spectrum.library.concordia.ca/9199/1/Rezk_2006.pdf.
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The use of multiple antennas at the transmitter and the receiver can significantly increase the data rate and reliability of communications over wireless channels. With constraints in practical implementations, transmission techniques are designed to achieve a certain trade-off between transmission rates and implementation complexity. Layered space time (LST) architecture achieves high data transmission rates in multiple-input multiple-output (MIMO) systems with reasonable complexity through separate multi-user detection and decoding. However, LST architecture is suboptimal since the redundancy in error correcting codes is not fully exploited in detection. This suggests improvements to the existing LST design are possible. Multi-level coding (MLC), which achieves the channel capacity based on the information chain rule, has been applied in MIMO communications for improved performance. In practice, however, rate optimization is difficult to implement. In this thesis, we consider improved LST architecture that provides better performance without increasing the implementation complexity. For improved performance, we propose the use of multi-stage decoding (MSD) in the LST receiver. The use of MSD exploits the inherent redundancy in error correcting codes in data detection and effectively applies the idea of multi-level coding (MLC). In addition, we propose unequal transmit power allocation to achieve equal capacities among layers. The introduction of transmit power as an additional dimension in design adds more flexibility to the design process and improves performance without increasing implementation complexity. Based on the notion of unequal power allocation, an improved LST architecture is proposed. The power allocation required to achieve equal capacities among layers in LST architecture is derived. The theoretical analysis of the proposed unequal power allocation is carried out for both fast and quasi-static fading channels based on different criteria. Performance analysis of the proposed approach is conducted and its practical implementation is discussed. It is shown that the proposed architecture is flexible in terms of implementation and offers a convenient trade-off between capacity and implementation complexity. The difference between achievable capacity in the proposed architecture and theoretical limits is negligible and converges to a constant at high SNR. Simulation results demonstrate that the proposed architecture provides significant performance gain as compared to existing LST architectures and approaches the near optimum bit-interleaved coded modulation (BICM) within a fraction of 1 dB
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Chang, Shi-Han, and 張仕翰. "Transmit Antenna Selection and Power Allocation in STBC-SM Hybrid Systems using Genetic Algorithm." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/52302786966140043225.
Full textAbstract:
碩士國立臺灣海洋大學
電機工程學系
99
Abstract Multiple-input Multiple-output (MIMO) antenna array system is used for improving data transmission rate and communication reliability, but it also increases hardware cost and operational complexity. The system that combines space-time block code (STBC) and spatial multiplexing (SM), called STBC-SM system, can find the tradeoff between data transmission rate and communication reliability. In this thesis, we investigate feasible schemes of transmit antenna selection and power allocation that can maximize channel capacity subject to a fixed amount of total transmitted power in a STBC-SM system. Antenna selection can reduce hardware complexity, whereas power allocation is able to improve channel capacity. As such, we propose a hybrid genetic algorithm in which a chromosome is composed of genes from two parts: the antenna selection part and the power allocation part. These chromosomes evolve to the next generation through steps of evaluation, selection, hybrid crossover and hybrid mutation until convergence is attained. The best combination of selected antennas with their allocated powers can be obtained from the best chromosome that produces the global optimal value of channel capacity. Finally, computer simulations are carried out to show that the proposed algorithm has lower operational complexity and larger channel capacity, as compared to the optimal antenna selection scheme. Keywords: MIMO, space-time block code-spatial multiplexing hybrid system, antenna selection, power allocation, channel capacity, genetic algorithm
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Chiu, Hsin-Yuan, and 邱信源. "Adaptive Bit and Power Allocation for OFDM under Power-Line Channels." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/27792820080513235246.
Full textAbstract:
碩士國立成功大學
電腦與通信工程研究所
93
The in-building low-voltage power-line networks are a convenient and low cost medium for digital communications. However, since power-line networks are not originally designed for communication, it may suffer from a lot of channel degradation and interference to transmit high-speed signals on them. In this thesis, we have studied the characteristics of power-line channel which include the various types of noises, the time-varying impedance and the attenuation. We have built a power-line channel model for simulations. We design a FEC coded system based on the HomePlug 1.0 Specification to reduce the effects of the narrowband interferences presented in the power-line networks. We propose a bit and power allocation scheme with low complexity to enhance the system capacity of the power-line communication at a target bit error rate.
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莊于禎. "Secondary Transmit Power Allocation for Cooperative Spectrum Sensing under K-out-of-N Decision Fusion." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/60534818353938056499.
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碩士國立交通大學
電信工程研究所
103
In a cognitive radio setting, this thesis studies transmit power allocation as well as local thresholds allocation for secondary users (SUs) with the aim of maximizing the global probability of detection at the fusion center (FC). This work considers hard decision (HD) based cooperative sensing (CS). Based on the received observations on the listening channel, each SU uses likelihood ratio test (LRT) to generate a binary decision and then sends to the FC over error-prone reporting channel. We assume the reporting channels are independent and identically distributed (i.i.d.) Rayleigh fading channels and the FC employs the majority rule to make a final decision. The exact formulae of the global probability of detection and global probability of false alarm at the FC are derived. Furthermore, when the reporting channels are in high SNR regime, we derived the analytic and approximate formulae of the global probability of detection and the global probability of false alarm at the FC. To improve detection performance in our system model, we formulate an optimization problem which could be described as follows: maximize the global probability of detection at the FC while satisfying global probability of false alarm and transmit power constraints. When comparing global probability of detection under uniform transmit power allocation with non-uniform transmit power allocation, simulation results show that improved detection performance at the FC is achieved.
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Lin, Yi-Yin, and 林益因. "Adaptive Power Allocation for Multi-Relays Cooperative OFDM Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/90077419740813665117.
Full textAbstract:
碩士國立暨南國際大學
通訊工程研究所
98
In this thesis, we study subcarrier power allocation problem for a cooperative orthogonal frequency division multiplexing system with amplify-and-forward (AF) relaying strategy. First, single relay node is considered in the cooperative system. An optimization problem, to achieve minimal average bit error rate at destination via power allocation among subcarriers in source and relay nodes under total transmission power constraint, is proposed. Two methods, namely KKT (Karush-Kuhn-Tucker) condition and Quasi-Newton method respectively, are used to solve the optimization problem. Simulation results are used to compare the average bit error rate performance between optimal power allocation case and equal power allocation case. Finally, the system architecture will be extended to multiple relay nodes and the power allocation issue among subcarriers in source and multiple relay nodes will be further investigated.
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Viswanathan, Hariharasudhan. "Adaptive transmit power control based on signal strength and frame loss measurements for WLANs." 2009. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052264.
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Wang, Jason, and 王禎毅. "Adaptive Power Allocation for 2 × n Space-Time Block Coding." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/59735888607332561354.
Full textAbstract:
碩士國立臺灣大學
電機工程學研究所
96
In this paper, we explore the application of adaptive power allocation to 2 × nr space-time block code (STBC) systems, where nr specifies an arbitrary number of antennas at the receiver. We demonstrated how a fixed amount of transmit power allocated among the transmit antennas in different quantities can result in an improved bit error rate (BER) performance. Using a feed-back link between the transmitter and receiver, adaptive power allocation can also be used to improve the system capacity or minimize the transmit power of a system while satisfying a threshold BER equirement. Our method for allocating the transmit power is compared with the conventional power allocation method of water-filling and with a hypothetical capacity-constrained waterfilling method. The case of imperfect channel estimation at the receiver is also analyzed for its effects on the performance of adaptive power allocation.
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Ji, Zhong-tian, and 季中天. "Power Allocation and Adaptive Modulation in AF-OFDM Relaying Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/88453908305588013235.
Full textAbstract:
碩士國立臺灣科技大學
電子工程系
98
Mobile WiMax has become the first choice of the 4G cellular network. It can meet newly smart phone, Mobil Internet Device (MID), and notebook’s transition requirement. Mobil WiMax provides high speed broadband with variety service, such as data, Voice over Internet Protocol (VoIP), and QoS Video Streaming. Its core technique is orthogonal frequency division multiplexing (OFDM), which can be used to support the requirement of mobile broadband in present time and in the future. In recent years, the concept of the relaying system transition is greatly applied to the high speed wireless communication service. It can be used to confront the shadowing and path loss while communicating, and then to reduce the bit error rate. Two primary kinds of relaying schemes are the amplify-and-forward (AF) relaying and the decode-and-forward (DF) relaying. Most of previous studies, which are related to relaying system research, assume that the transition power between source and relay can be switched when satisfying the limitation of system’s total power. However, few studies discuss the situation that the source and the relay has their own total power constraint. Hence, we add individual power constraints to the source and the relay, respectively. In this thesis, we combine OFDM technique and amplify-and-forward (AF) relaying. We propose a power allocation mechanism to achieve the minimal average bit error rate and propose adaptive modulation to raise the data transmission speed of system. We assume that there is perfect channel state information between the source and the relay. We take into consideration that the source-to-relay part and the relay-to-destination part go through different frequency selective fading. In the scheme of power allocation, we use Lagrange’s method to get the solution. We, then, set the result of power allocation as the initialization value of adaptive modulation. In the condition of satisfying power constraint and service quality, we use the coefficient of signal-to-noise-rate and the relay to calculate the minimal power of every subcarrier needed when they use higher-level modulations, with which the transmission speed is raised.
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Peng, Chien-Fan, and 彭建帆. "Grouping and Power Allocation for Adaptive Modulation in Multichannel Communications." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/81098795632009718623.
Full textAbstract:
碩士國立臺灣科技大學
電子工程系
97
The technique of multichannel communication has been intensely investigated in recently years. It offers the feasibility to take into account the different characteristics of different subchannels and thus make the best use of them, typically achieved by adopting adaptive modulation/coding (AMC) schemes and also by power allocation (PA) for the subchannels. One difficulty with the afore-mentioned AMC-PA problem is that the computation complexity becomes prohibitively high as the number of subchannels grows. In this thesis, we try to reduce the computation complexity in the AMC-PA problem, through a method that we call the grouping scheme, wherein the subchannels are divided into a few groups. The same modulation scheme is adopted for all the subchannels in the same group. The grouping scheme consists of three stages. In the first stage, the subchannels are divided into a few groups, wherein each group consists of all the subchannels whose fading gains are close to each other. Then, a modulation scheme is chosen, according to a data rate maximization algorithm, for each group. In the mean time, the power allocated to each group is also computed. The second stage is regrouping, wherein the modulation of the best subchannel in a group has a chance to be upgraded. The third stage is an energy recycling mechanism, through which the bit error rates are lowered. Experimental results show that our regrouping mechanism can achieve a data rate very close to the optimum value (achieved when each subchannel is treated as a single group of its own). At the price of this slight decrease in data transmission rate, however, the computation complexity is greatly reduced.
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Wang, Jason. "Adaptive Power Allocation for 2 * n Space-Time Block Coding." 2008. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-2807200800211700.
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"Frequency allocation, transmit power control, and load balancing with site specific knowledge for optimizing wireless network performance." Thesis, 2007. http://hdl.handle.net/2152/3016.
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Chen, Jeremy Kang-pen. "Frequency allocation, transmit power control, and load balancing with site specific knowledge for optimizing wireless network performance." 2007. http://hdl.handle.net/2152/13184.
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Huang, Shen-chia, and 黃聖嘉. "Genetic Algorithm-Assisted Joint Precoding and Transmit Antenna Selection with Power Allocation in Multi-user MIMO Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/19079209904591594505.
Full textAbstract:
碩士國立臺灣科技大學
電子工程系
98
Multiple-input multiple-output (MIMO) systems are one of the potential promises to meet the rapidly growing demand for higher transmission data rates and better quality of service (QoS) for wireless communications. However, deploying a large number of antennas in MIMO systems also incurs two setbacks. First, the hardware cost will increase. Second, the interference impairment becomes more pronounced. Many enabling technologies have been developed to alleviate these inevitable setbacks. Since the precoding can compensate for the loss of array gain during antenna selection and the antenna selection can offset the degradation of diversity in the precoding, it is advantageous to combine both techniques to enhance the overall system performance. In this thesis we propose a simple and efficient genetic algorithm-assisted approach for simultaneously selecting the quantized precoding vectors and the transmit antenna subset in the downlink of multi-user MIMO systems with limited feedback. We then extend this GA approach to joint optimal precoding and transmit antenna selection when perfect channel state information (CSI) is available at the base station (BS). The power allocation is taken into consideration as a whole to further enhance the system performance. In the new GA approaches, each chromosome can be divided into a bit string for quantized/optimal precoding, an integer string for transmit antenna selection, and a bit string for power allocation. In addition, new crossover and mutation operations are addresses to accommodate these new chromosomes. Furnished simulations show that the proposed new GA approaches indeed yield superior performance with reduced computational complexity overhead compared with previous works in various scenarios.
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Lin, Yu-Cheng, and 林裕盛. "Adaptive Power Allocation Schemes in Relay Stations for Cooperative OFDM Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/24904223775808852876.
Full textAbstract:
碩士東海大學
電機工程學系
98
In recent years, cooperative communications have become more and more popular. Cooperative communications improve the transmission quality with the concept of special diversity. The orthogonal frequency division multiplexing (OFDM) has been selected to be the primary technology in the next generation communication system because of high data transmission rate and resistance to selective fading channel. Therefore, we do researches on subcarrier power allocation problems with combination of cooperative communication and orthogonal frequency division multiplexing technology. We study three optimization problems in single relay node environment. First, the optimal power allocation problem at the relay node is performed. Here, equal power allocation for each subcarrier at the source node is assumed. Second, the optimal power allocation problem at the source node under equal power allocation at the relay node is investigated. Finally, the optimal power allocation problem at both source and relay nodes simultaneously is studied. As for the three problems, the optimization goal is to minimize the average bit error rate by proper subcarrier power allocation under the constraint of finite total power at source node and relay node respectively. Performance comparisons among three optimization problems are carried out using Quasi-Newton BFGS method.
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Carvalho, Barbosa Silva Yuri. "Adaptive beamforming and power allocation in multi-carrier multicast wireless networks." Phd thesis, 2008. http://tuprints.ulb.tu-darmstadt.de/1008/1/thesis_silva_multicast.pdf.
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In the context of next-generation wireless systems, it is expected that services targeted at mass content distribution become widely popular, which is reflected for instance in the standardization activities for their implementation within current cellular networks. Examples of such services are audio/video streaming, mobile TV, messaging, news clips, localized services, download, among others. Their common characteristic is that the same information has to be transmitted to a group of users (multicast) or to all users (broadcast) within a certain coverage area. This thesis deals with the problem of multicast beamforming for multi-antenna wireless cellular networks. Both single-group and multi-group scenarios are taken into account, with the former corresponding to a single multicast group per radio resource and the latter referring to multiple multicast groups per resource. In order to provide the necessary mathematical framework for the analysis of the algorithms, a general system model is proposed for the multi-group multicast scenario. Particular cases, such as the multi-user, single-group, and single-user cases, can be derived from the general model by properly adjusting the system parameters. Different beamforming algorithms known from the unicast case are formulated for the single-group multicast case. Moreover, a new algorithm termed USMF specifically designed for the multicast case is proposed, which is shown to provide a good trade-off between performance and complexity. For the multi-group multicast case, the resource sharing results in inter-group interference, which needs to be suppressed by the beamforming algorithms. Linear and non-linear algorithms known from the unicast case are formulated for the multi-group multicast scenario. These algorithms are also further modified with the purpose of improving the performance of the multicast services. The strategies proposed for both single-group and multi-group cases are analyzed in terms of their performance and computational complexity. Finally, since the allocation of resources among the multicast groups is expected to have a significant impact on the performance of the beamforming algorithms, this issue is addressed as well. The analysis focuses on the proposal and evaluation of different alternatives for allocating the power among the subcarriers of a multi-carrier single-group multicast system. One of these alternatives is an extension of the traditional unicast waterfilling algorithm for the multicast case. Additionally, some considerations are made with regard to the allocation of resources in multi-carrier multi-group multicast scenarios. It is shown that, in spite of the inter-group interference, the sharing of resources among unicast and multicast users provides better performance than isolating them into different resources.
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Lin, Yu-Lun, and 林佑倫. "Adaptive Power Allocation over Narrowband PowerLine Communication under Class-A Interference." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/36515171986694776732.
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碩士國立清華大學
電機工程學系
101
The ozone layer has been destructed for a long time and eco-tech gets more discussions and attention. Effective resource management in the world become more important. Power management is one important issue of green technology. Through the rapid demand of smart power use and management, issues of power line gradually gets more concern. Smart Grid, which rely on mass power line infrastructure, has rapid development in recent years. An energy-efficiency and real-time power management is critical now and ever. Hence, power line communication (PLC) becomes widely discussed these years. The use of power line distribution grid for data communication has gained lot of interest over the past several years. By establishing communication on the same power line infrastructure that delivers electricity, there is no need to create new communication paths through obstacles such as buildings, hills. Thus, installation and maintenance costs are lower than Ethernet or wireless communication. Nevertheless, PLC suffer many challenges such as multi-path fading, and time-varying impulse noise, which is modeled as class-A noise in this thesis. The proposed receiver solve most of the problem. Unfortunately, impulse noise is sometimes the most system degradation factor that cause transmission fail. Many works shows adding certain processor to deal with it for some system enhancement. For instance, impulse noise suppressor or Viterbi preprocessor is added is their designed receiver. However, lots of hardware overhead are simultaneously produced. Resource allocation is a useful and effective way to improve the system without much hardware overhead. A proposed power allocation/loading scheme added in my transmitter is for reducing the signal distortion by fading and impulse noise. A well-known method to improve data rate about bis/power allocation/loading is waterfilling algorithm. By contrary, my work prefer to ii provide power-saving or bit error rate (BER) improvement Both standards, PRIME and G3- PLC are tested with my algorithms ad others. In severe class-A noise channel, my solution provides 5dB gain over the best power algorithms in class-A scheme and 0.2 dB in well class- A noise channel for PRIME system. In G3-PLC, there’re about 2.8 dB and 0.1dB respectively. This reveals my algorithms is strongly applied in severe class-A case.
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Hong, Cheng-You, and 洪承佑. "Implementation of Proprietary Wireless Communication Protocol with Adaptive Power Control and Channel Allocation." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/98866852481818608670.
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碩士龍華科技大學
電子工程系碩士班
104
In this thesis, we develop a new or noval proprietary wireless transmission protocol for solving the interference problems. There are two tasks involved in the protocol. One of them involved with the adaptive radiation power control according to the received RSSI signal strength. The other one, based on the information of SNR of various RF channels, use the frequency hopping techniques to allocate RF channels adaptively. The ARM processor, STM32F429ZIT, with clock frequency up to 180MHz is used for algorithm implementation in this work. Both ADI 's FSK/GFSK ADF7242, zero IF transceiver (ADF7242) at 2.4GHz, and Avago's MGA83563 power amplifier (MGA83563) with gain up to 23dB are used for RF implementation. The error correction code will be included in this wireless communication system. The (15,11) Hamming code appended with one extra parity check bit will be used to correct one bit error and to detect error bits larger than or equal to 2 within a frame of 16 bits. From the actual measurements, the BER of data transmission can be reduced about 0.1% with adding the adaptive power control technique only and reduced about 0% via addlying automatic frequency hopping technique only. Besides, using both techniques on the proprietary communication system, the BER of data transmission is reduced from 0% to 0.05%
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Lu, Yun-teng, and 呂允騰. "Genetic Algorithm Approach for Adaptive Subcarrier, Bit, and Power Allocation in OFDM System." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/9ued95.
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碩士國立中央大學
通訊工程研究所碩士在職專班
96
In this thesis, we proof Genetic Algorithm(GA) and Evolution strategy(ES) performance better than general suboptimal algorithms(Constructive Initial assignment and Dynamic Channel Allocation) in Margin Adaptive Optimization(MA) problem based on OFDM communication system, cause GA and ES algorithms can jump out of local minimum easier than general suboptimal algorithms. We continue to compare with GA and ES algorithms in both of them add Fuzzy Logic Controller(FLC) and extension method. Simulation results show that, GA and ES get better performance than before, and in the same condition GA has the same performance with ES in specific gene length setting.
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Lai, Hung-Chin, and 賴宏晉. "Adaptive Power Allocation under Target Bit Error Rate Constraint for Cooperative OFDM Systems." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/86089341873826627823.
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碩士建國科技大學
電機工程系暨研究所
102
The research purpose in this dissertation aims to investigate the algorithms of adaptive resource allocation on OFDM-based (Orthogonal Frequency Division Multiplexing) cooperative communication systems and amplify-and-forward on the cooperative protocol. In the single source, relay and destination node environment to investigated the power allocation problem for the subcarriers of the source node. The research for this article under total power and target BER constraints is to maximize the total system throughput by power allocation at the subcarriers of the source node. We used Lagrange multiplier method with KKT (Karush-Kuhn-Tucker) conditions to solve the optimal power allocation for the subcarriers of the source node and derive optimized source subcarrier power allocation. Based the computational complexity of the optimal algorithm that a subcarrier pair algorithm about subcarrier power allocation of the source node was designed to maximize system throughput and reduce computational complexity. The goal of the subcarrier pair algorithm under total power and target BER constraints is to maximize the total system throughput by power allocation at the subcarrier pair of the source node.
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Chiu, Ying-Hsuan, and 邱盈瑄. "Performance Improvement of Adaptive Resource Allocation Algorithm Based on Minimum Power Criterion in OFDMA Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/4ktd27.
Full textAbstract:
碩士國立臺北科技大學
電機工程系所
98
The adaptive resource allocation algorithm based on minimum power criterion in OFDMA system is an algorithm with both proportional rate constraint and fixed total user’s power. First, the number of subcarriers for each user is determined by considering the factors of both proportional rate constraint and near-far effect. Then the subcarriers for each user are allocated based on minimum power criterion. Compared with other algorithms, this algorithm has high transmission capacity, but the complexity would increase when the number of users increases. This thesis mainly focuses on improving the complexity of this algorithm. We set up a threshold that based on the average of minimum transmission power for each subcarriers. Thus some subcarriers with lower SNR will be eliminated to improve the speed of subcarrier allocation. The computer simulation shows that our proposed algorithm, compared with other three algorithms, can efficiently reduce the complexity without influencing the capacity of transmission.
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Silva, Yuri Carvalho Barbosa [Verfasser]. "Adaptive beamforming and power allocation in multi-carrier multicast wireless networks / von Yuri Carvalho Barbosa Silva." 2008. http://d-nb.info/99382174X/34.
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Wang, Shih-Wei, and 王士瑋. "Adaptive Bit, Power and Spreading Factor Allocation Algorithms for Multi-carrier CDMA Communication Systems on Reverse Link." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/65521543561249518963.
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碩士國立中央大學
通訊工程研究所
93
By using the successive interference cancellation (SIC) receiver, we can simplify the situation, the power of users are affected mutually. Based on the simplification, we propose bit, power and spreading factor (SF) allocation algorithms for Multi-carrier CDMA (MC-CDMA) communication systems in uplink transmission. Assuming that the channel estimation of all sub-carriers of all users are perfect, one of the proposed algorithms tries to maximize the sum of data rates of the users in the system while satisfying the power and bit error rate (BER) constraints of each user, and the other algorithm tries to minimize the required transmission power while satisfying the rate requirement and BER constraint of each user. These novel algorithms determine bit, power and SF allocation simultaneously. The proposed schemes offer better performance than the fixed SF and modulation system as demonstrated in the simulation results.
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Huang, Jen-Ya, and 黃楨雅. "An Adaptive Bit, Subcarrier, Power, and Spreading Factor Allocation Algorithm for Multicarrier DS-CDMA Communication Systems on Forward Links." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/84320096300355537804.
Full textAbstract:
碩士國立中央大學
通訊工程研究所
92
In this paper, we propose a real-time bit, subcarrier, power, and spreading factor allocation algorithm for MC DS-CDMA communication system in forward link transmission. Assuming that base stations know the channel gain of all subcarriers of all users, the proposed loading algorithm tries to minimize the required transmit power while satisfying the rate requirement and data error rate constraint of each other. The novel algorithm determines bit, subcarrier, power, and spreading factor allocation simultaneously by the combination of DBA algorithm and spreading factor parameter. The proposed scheme offers better performance in the terms of transmit power than [7][9], as demonstrated in the simulation results.
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Tien, Fengyu, and 田豐瑜. "Improving the Throughput Performance by Adaptive Power Allocation to Femto BS Channels in Next-Generation Hybrid Macrocell/Femtocell Networks." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/36270299636880398958.
Full textAbstract:
碩士國立中正大學
通訊工程研究所
99
Due to the increase of smart mobile phone users and more and more multimedia streaming and new Internet services, the 3rd-generation mobile communication system is running out of gas, which triggers the development of the higher-speed 4th -generation (4G) mobile communication system . The International Tele- communication Union (ITU) is actively working on finalizing the technical standards for 4G. The standards require 4th-generation service to support data rate at 100 Mbit/s for high mobility communication and 1 Gbit/s for stationary communication. WiMAX (802.16m) and LTE Advanced are two 4G standards that are being developed now. In them,the femto base stations are defined as small low-power cellular base stations, deployed by the user at home, without complicated configuration and using DSL or cable modem of different telecommunications operators to connect to the Internet. The 4G system improves signal coverage and dead area problem of indoor users by provisioning a large number of femto base stations. It also improves the total system throughput. In the thesis, we consider some drawbacks of average power allocation to femto BS channels in the fourth-generation system, and then utilize the multi-carrier characteristic of the orthogonal frequency-division multiple access (OFDMA) to improve the throughput performance by adaptive power allocation to femto BS channels in next-generation hybrid macrocell/femtocell networks. We will compare the performances of average power allocation and adaptive power allocation in different channel assignment and femtocell density settings. Keyword: fourth-generation, femto base stations, adaptive power allocation
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Tsai, Tzung-Shiun, and 蔡宗訓. "Efficient Prediction-based AMC Selection with Adaptive MIMO Power Allocation to Increase System Capacity in IEEE 802.16 WiMAX Networks." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/34809920672903873721.
Full textAbstract:
碩士朝陽科技大學
資訊工程系碩士班
98
The multiple-input and multiple-output (MIMO) scheme specified in IEEE 802.16m is proposed to provide high data rate and high transmission quality while enabling compatible with the existing IEEE 802.16 family. However, the system suffers from high mobility and various-type of wireless interferences, because the quality of wireless-channels in MIMO significantly affects the determination of modulation and coding scheme (MCS) and the performance. The system capacity and the MCS selection are thus degraded significantly. This thesis thus proposed a prediction-based MCS selection with adaptive MIMO power allocation to increase the system capacity, while overcoming these disadvantages. In addition, a MCS hysteresis scheme is proposed to avoid unnecessary MCS change and to minimize the overhead of changing MCSs. Numerical results indicate that the proposed approach significantly outperforms the compared approaches in system capacity, the probability of MCS change, and the accuracy of MCS determination.
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Du, Qinghe. "Adaptive Resource Allocation for Statistical QoS Provisioning in Mobile Wireless Communications and Networks." Thesis, 2010. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8884.
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Due to the highly-varying wireless channels over time, frequency, and space
domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has
become a recognized feature in the next-generation wireless networks. In this dissertation,
we study the adaptive wireless resource allocation problems for statistical QoS
provisioning, such as guaranteeing the specified delay-bound violation probability,
upper-bounding the average loss-rate, optimizing the average goodput/throughput,
etc., in several typical types of mobile wireless networks.
In the first part of this dissertation, we study the statistical QoS provisioning for
mobile multicast through the adaptive resource allocations, where different multicast
receivers attempt to receive the common messages from a single base-station sender
over broadcast fading channels. Because of the heterogeneous fading across different
multicast receivers, both instantaneously and statistically, how to design the efficient
adaptive rate control and resource allocation for wireless multicast is a widely cited
open problem. We first study the time-sharing based goodput-optimization problem
for non-realtime multicast services. Then, to more comprehensively characterize the
QoS provisioning problems for mobile multicast with diverse QoS requirements, we
further integrate the statistical delay-QoS control techniques — effective capacity
theory, statistical loss-rate control, and information theory to propose a QoS-driven
optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS
requirements, sustainable traffic load, and the average loss rate through the adaptive
resource allocations and queue management. Furthermore, we study the adaptive
resource allocation problems for multi-layer video multicast to satisfy diverse statistical
delay and loss QoS requirements over different video layers. In addition,
we derive the efficient adaptive erasure-correction coding scheme for the packet-level
multicast, where the erasure-correction code is dynamically constructed based on multicast
receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile
multicast networks.
In the second part of this dissertation, we design the adaptive resource allocation
schemes for QoS provisioning in unicast based wireless networks, with emphasis
on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and
power allocation schemes for multi-user downlink transmissions (with independent
messages) in cellular networks to maximize the delay-QoS-constrained sum system
throughput. Second, we propose the delay-QoS-aware base-station selection schemes
in distributed multiple-input-multiple-output systems. Third, we study the queueaware
spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning.
Analyses and simulations are presented to show the advantages of our proposed
schemes and the impact of delay-QoS requirements on adaptive resource allocations
in various environments.
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Gururaja, Srinivas. "Joint optimal pilot placement and power allocation with space frequency code design and adaptive modulation for video transmission over MIMO-OFDM systems." 2007. http://proquest.umi.com/pqdweb?did=1417814041&sid=8&Fmt=2&clientId=39334&RQT=309&VName=PQD.
Full textAbstract:
Thesis (M.S.)--State University of New York at Buffalo, 2007.Title from PDF title page (viewed on Feb. 19, 2008) Available through UMI ProQuest Digital Dissertations. Thesis adviser: Liu, Pao-Lo. Includes bibliographical references.
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Nguyen, Dang Khoa. "Adaptive transmission for block-fading channels." 2010. http://arrow.unisa.edu.au:8081/1959.8/96822.
Full textAbstract:
Multipath propagation and mobility in wireless communication systems give rise to variations in the amplitude and phase of the transmitted signal, commonly referred to as fading. Many wireless applications are affected by slowly varying fading, where the channel is non-ergodic, leading to non-reliable transmission during bad channel realizations. These communication scenarios are well modeled by the block-fading channel, where the reliability is quantatively characterized by the outage probability. This thesis focuses on the analysis and design of adaptive transmission schemes to improve the outage performance of both single- and multiple-antenna transmission over the block-fading channel, especially for the cases where discrete input constellations are used. Firstly, a new lower bound on the outage probability of non-adaptive transmission is proposed, providing an efficient tool for evaluating the performance of non-adaptive transmission. The lower bound, together with its asymptotic analysis, is essential for efficiently designing the adaptive transmission schemes considered in the thesis. Secondly, new power allocation rules are derived to minimize the outage probability of fixed-rate transmission over block-fading channels. Asymptotic outage analysis for the resulting schemes is performed, revealing important system design criteria. Furthermore, the thesis proposes novel suboptimal power allocation rules, which enjoy low-complexity while suffering minimal losses as compared to the optimal solution. Thus, these schemes facilitate power adaptation in low-cost devices. Thirdly, the thesis considers incremental-redundancy automatic-repeat-request (INR-ARQ) strategies, which perform adaptive transmission based on receiver feedback. In particular, the thesis concentrates on multi-bit feedback, which has been shown to yield significant gains in performance compared to conventional single-bit ARQ schemes. The thesis proposes a new information-theoretic framework for multi-bit feedback INR-ARQ, whereby the receiver feeds back a quantized version of the accumulated mutual information. Within this framework, the thesis presents an asymptotic analysis which yields the large gains in outage performance offered by multi-bit feedback. Furthermore, the thesis proposes practical design rules, which further illustrates the benefits of multi-bit feedback in INR-ARQ systems. In short, the thesis studies the outage performance of transmission over block-fading channels. Outage analysis is performed for non-adaptive and adaptive transmission. Improvements for the existing adaptive schemes are also proposed, leading to either lower complexity requirements or better outage performance. Still, further research is needed to bring the benefits offered by adaptive transmission into practical systems.Thesis (PhD)--University of South Australia, 2010
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Choi, Eun Ho. "Study of efficient link adaptation schemes in wireless orthogonal frequency division multiplexing (OFDM) systems." 2009. http://hdl.handle.net/2152/6565.
Full textAbstract:
Wireless communication systems require high spectral efficiency and throughput in order to be cost-effective. Link adaptation schemes are known to be a good solution to achieve this goal. However, the necessity of additional information or increased complexity prevents these schemes from being implemented. In this context, research on resource allocation based on different constraints, such as complexity or feedback, is important. The major contribution of this dissertation is the development of three novel techniques to enhance performance in practical implementations of the adaptive OFDM systems. This dissertation first introduces a new multiuser OFDM system to enhance performance in the low SNR regime. In this scheme, multiuser diversity can be efficiently amplified from random power allocation and opportunistic scheduling. Higher spectral efficiency can be achieved without an increase of complexity or feedback amount compared to conventional multiuser OFDM systems using equal power allocation. This dissertation also presents a modified multi-mode power loading scheme. A modified multi-mode power loading scheme can circumvent the limit of current multi-mode power loading schemes by significantly reducing search amount from 2N - 1 to N, where N is the number of subcarriers. Finally, this dissertation has introduced adaptive OFDM systems using channel gain order information in limited feedback environments. Adaptive OFDM systems using the order mapping technique achieve comparable performance to conventional adaptive OFDM systems in terms of bit error rate and average spectral efficiency, while the amount of feedback is significantly reduced. Furthermore, by simply exploiting order mapping and interpolation, the analyzing technique circumvents the practical shortcomings of previous limited feedback techniques for OFDM systems.text