Dissertations / Theses on the topic 'Multiple Active Spatial Modulation'

Spatial modulation (SM) is a transmission technique proposed for multiple–input multiple– output (MIMO) systems, where only one transmit antenna is active at a time, offering an increase in the spectral efficiency equal to the base–two logarithm of the number of transmit antennas. The activation of only one antenna at each time instance enhances the average bit error ratio (ABER) as inter–channel interference (ICI) is avoided, and reduces hardware complexity, algorithmic complexity and power consumption. Thus, SM is an ideal candidate for large scale MIMO (tens and hundreds of antennas). The analytical ABER performance of SM is studied and different frameworks are proposed in other works. However, these frameworks have various limitations. Therefore, a closed–form analytical bound for the ABER performance of SM over correlated and uncorrelated, Rayleigh, Rician and Nakagami–m channels is proposed in this work. Furthermore, in spite of the low–complexity implementation of SM, there is still potential for further reductions, by limiting the number of possible combinations by exploiting the sphere decoder (SD) principle. However, existing SD algorithms do not consider the basic and fundamental principle of SM, that at any given time, only one antenna is active. Therefore, two modified SD algorithms tailored to SM are proposed. It is shown that the proposed sphere decoder algorithms offer an optimal performance, with a significant reduction of the computational complexity. Finally, the logarithmic increase in spectral efficiency offered by SM and the requirement that the number of antennas must be a power of two would require a large number of antennas. To overcome this limitation, two new MIMO modulation systems generalised spatial modulation (GNSM) and variable generalised spatial modulation (VGSM) are proposed, where the same symbol is transmitted simultaneously from more than one transmit antenna at a time. Transmitting the same data symbol from more than one antenna reduces the number of transmit antennas needed and retains the key advantages of SM. In initial development simple channel models can be used, however, as the system develops it should be tested on more realistic channels, which include the interactions between the environment and antennas. Therefore, a full analysis of the ABER performance of SM over urban channel measurements is carried out. The results using the urban measured channels confirm the theoretical work done in the field of SM. Finally, for the first time, the performance of SM is tested in a practical testbed, whereby the SM principle is validated.

Spatial Modulation (SM) is a Multiple-Input Multiple-Output (MIMO) transmission technique which realizes low complexity implementations in wireless communication systems. Due the transmission principle of SM, only one Radio Frequency (RF) chain is required in the transmitter. Therefore, the complexity of the transmitter is lower compared to the complexity of traditional MIMO schemes, such as Spatial MultipleXing (SMX). In addition, because of the single RF chain configuration of SM, only one Power Amplifier (PA) is required in the transmitter. Hence, SM has the potential to exhibit significant Energy Efficiency (EE) benefits. At the receiver side, due to the SM transmission mechanism, detection is conducted using a low complexity (single stream) Maximum Likelihood (ML) detector. However, despite the use of a single stream detector, SM achieves a multiplexing gain. A point-to-point closed-loop variant of SM is receive space modulation. In receive space modulation, the concept of SMis extended at the receiver side, using linear precoding with Channel State Information at the Transmitter (CSIT). Even though receive space modulation does not preserve the single RF chain configuration of SM, due to the deployed linear precoding, it can be efficiently incorporated in a Space Division Multiple Access (SDMA) or in a Virtual Multiple-Input Multiple-Output (VMIMO) architecture. Inspired by the potentials of SM, the objectives of this thesis are the evaluation of the EE of SM and its extension in different forms of MIMO communication. In particular, a realistic power model for the power consumption of a Base Station (BS) is deployed in order to assess the EE of SM in terms of Mbps/J. By taking into account the whole power supply of a BS and considering a Time Division Multiple Access (TDMA) multiple access scheme, it is shown that SM is significantly more energy efficient compared to the traditional MIMO techniques. In the considered system setup, it is shown that SM is up to 67% more energy efficient compared to the benchmark systems. In addition, the concept of space modulation is researched at the receiver side. Specifically, based on the union bound technique, a framework for the evaluation of the Average Bit Error Probability (ABEP), diversity order, and coding gain of receive space modulation is developed. Because receive space modulation deploys linear precoding with CSIT, two new precoding methods which utilize imperfect CSIT are proposed. Furthermore, in this thesis, receive space modulation is incorporated in the broadcast channel. The derivation of the theoretical ABEP, diversity order, and coding gain of the new broadcast scheme is provided. It is concluded that receive space modulation is able to outperform the corresponding traditional MIMO scheme. Finally, SM, receive space modulation, and relaying are combined in order to form a novel virtual MIMO architecture. It is shown that the new architecture practically eliminates or reduces the problem of the inefficient relaying of the uncoordinated virtual MIMO space modulation architectures. This is undertaken by using precoding in a novel fashion. The evaluation of the new architecture is conducted using simulation and theoretical results.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California
Direct spatial antenna modulation (DSAM) is a new approach to phased array control that opens up new "smart antenna" architecture possibilities. The DSAM technique leverages the inherent spatial differences of excitation in an antenna in a novel way to achieve the equivalent of conventional modulation and beam control effects. Smart antenna techniques are of potentially increasing importance to test range operations given a trend toward more flexible, internetworked, and autonomous test activities. The DSAM technique has been demonstrated through several generations of analysis, simulation, and prototyping, but has previously only been applied to narrowband antenna designs. Furthermore, the IQ DSAM approach in particular has not been previously implemented in hardware. This paper details the application of IQ DSAM to achieve wideband phase control using a commercial off the shelf (COTS) antenna. The phase control performance of IQ DSAM over a range of 1.5 GHz to 4 GHz is measured across relative field control angles of +/- 45 degrees. The measured IQ DSAM performance is compared to what could be expected from a conventional phased array element control architecture.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, Dec. 2004.
Thesis advisor(s): Murali Tummala, Roberto Cristi. Includes bibliographical references (p. 69-71). Also available online.

In order to meet the ever-growing demand for mobile data, a number of different technologies have been adopted by the fourth generation standardization bodies. These include multiple access schemes such as spatial division multiple access (SDMA), and efficient modulation techniques such as orthogonal frequency division multiplexing (OFDM)-based modulation. The specific objectives of this theses are to develop an effective feedback method for interference management in smart antenna SDMA systems and to design an efficient OFDM-based modulation technique, where an additional dimension is added to the conventional two-dimensional modulation techniques such as quadrature amplitude modulation (QAM). In SDMA time division duplex (TDD) systems, where channel reciprocity is maintained, uplink (UL) channel sounding method is considered as one of the most promising feedback methods due to its bandwidth and delay efficiency. Conventional channel sounding (CCS) only conveys the channel state information (CSI) of each active user to the base station (BS). Due to the limitation in system performance because of co-channel interference (CCI) from adjacent cells in interference-limited scenarios, CSI is only a suboptimal metric for multiuser spatial multiplexing optimization. The first major contribution of this theses is a novel interference feedback method proposed to provide the BS with implicit knowledge about the interference level received by each mobile station (MS). More specifically, it is proposed to weight the conventional channel sounding pilots by the level of the experienced interference at the user’s side. Interference-weighted channel sounding (IWCS) acts as a spectrally efficient feedback technique that provides the BS with implicit knowledge about CCI experienced by each MS, and significantly improves the downlink (DL) sum capacity for both greedy and fair scheduling policies. For the sake of completeness, a novel procedure is developed to make the IWCS pilots usable for UL optimization. It is proposed to divide the optimization metric obtained from the IWCS pilots by the interference experienced at the BS’s antennas. The resultant new metric, the channel gain divided by the multiplication of DL and UL interference, provides link-protection awareness and is used to optimize both UL and DL. Using maximum capacity scheduling criterion, the link-protection aware metric results in a gain in the median system sum capacity of 26.7% and 12.5% in DL and UL respectively compared to the case when conventional channel sounding techniques are used. Moreover, heuristic algorithm has been proposed in order to facilitate a practical optimization and to reduce the computational complexity. The second major contribution of this theses is an innovative transmission approach, referred to as subcarrier-index modulation (SIM), which is proposed to be integrated with OFDM. The key idea of SIM is to employ the subcarrier-index to convey information to the receiver. Furthermore, a closed-form analytical bit error ratio (BER) of SIM OFDM in Rayleigh channel is derived. Simulation results show BER performance gain of 4 dB over 4-QAM OFDM for both coded and uncoded data without power saving policy. Alternatively, power saving policy maintains an average gain of 1 dB while only using half OFDM symbol transmit power.

A novel energy efficient Multiple-Input-Multiple-Output (MIMO) technique is called Spatial Mod- ulation (SM). It uses only one radio frequency (RF) chain that reduces the hardware complexity and cost of the system. The concept of SM is to transmit the data information using modulation constellation and spatial constellation. It increases the spectral efficiency by keeping only one an- tenna active per every symbol period. Spatial Multiplexing (SMX) uses equal number of RF chains with transmit antennas that increases the hardware complexity and cost of the system. SM is free from Inter Channel Interference (ICI) and Inter Symbol Interference (ISI). Generalised Spatial Modulation (GSM) and Multiple Active Spatial Modulation (MASM) techniques were developed to increase the spectral efficiency of SM by increasing the number of RF chains. In GSM, the same modulation symbol transmits on different antennas hence, it avoids ISI. In MASM, multiple symbols are transmitted on different antenna con guration. A modi ed version of SM technique called Quadrature Spatial Modulation (QSM) uses both in-phase and quadrature dimensions to transmit the data symbol in one time instant. Hence, QSM enhance the spectral efficiency over SM. Recently, Generalised QSM (GQSM) scheme was developed to increase spectral efficiency by grouping the transmit antennas according to QSM principle. We propose a modi ed Generalised QSM (mGQSM) scheme without antenna grouping and we use multiple RF chains to enhance the spectral efficiency. The proposed scheme provides ex- tra one bit per channel use (bpcu) spectral efficiency over GQSM scheme with the constraint of flog2 Nt Nrf g 0:5, where f g denotes the fractional part of the decimal value, Nt denotes number of transmit antennas, and Nrf denotes number of RF chains. In mGQSM system, multiple data symbols are divided into real and imaginary parts and these parts are transmitted as in-phase and quadrature components by selecting any possible antenna activation patterns available in mGQSM, resulting in the choice of antenna activation patterns being doubled in mGQSM compared to GQSM which yields the extra one bpcu spectral efficiency over GQSM. Using the ML detection algorithm, we study the performance via numerical simulations using half code rate convolutional encoder at the transmitter and Viterbi decoding algorithm at the receiver to estimate the transmitted bits. We compute the computational complexity of ML- decoding in terms of real valued multiplications and introduce a variant of mGQSM called Reduced Codebook mGQSM (RC-mGQSM) to reduce the complexity by decreasing the spectral efficiency. In summary, a novel scheme mGQSM is proposed which improves the spectral efficiency of known scheme, GQSM by one bpcu.

碩士
國立中正大學
通訊工程研究所
105
In the spatial modulation multiple input multiple output (SM-MIMO) system, the best detector is the maximum likelihood detector (MLD). But MLD has the problem of high computational complexity and is not easily implemented by hardware architecture. Therefore many detection algorithms that are of low computational complexity and error rate performance close to theMLD are studied. Extension of the conventional SM-MIMO system to use multiple active transmit antenna for transmitting different symbols is called multiple active-spatial modulation (MA-SM). Low complexity linear detection algorithm of MA-SM signals are comprised of two steps. In the first step, estimation of the L groups of active antennas is performed; and, detection of the transmit symbols from the estimated groups of active antennas is performed in the second step. Unlike the joint detection, such separate detection of the active antennas and transmit symbols is of low complexity at the expense of performance degradation. For the hardware implementation, a 4-by-4 MIMO system with two active antennas transmitting 16-QAM signals is considered. The number of groups L is set to 2. The fixed point simulation results suggest that word length of the proposed architecture is 13 bits. The proposed design is described by Verilog HDL and synthesized by Synoposis Design Compiler.

碩士
國立交通大學
電信工程研究所
102
Spatial modulation in MIMO system (SM-MIMO) is a promising approach due to its low complexity and high energy efficiency properties. To enhance the SM-MIMO system performance, precoding at transmitter is shown to be effective. In this thesis, we investigate the precoder design techniques. With channel state information at transmitter, we propose two general precoder designs, including the problem formulations and its iterative algorithm, by manipulating the distance between codewords using optimization techniques. The designs can be virtually used in any type of SM-MIMO system. For practical concerns, codebook-based precoding is then introduced for SM-MIMO systems with limited feedback. To construct the effective codebook, we investigate the design criterion and propose three codebook design algorithms with different design considerations through exploiting the vector quantization techniques to maximize the average distance among codewords. Finally, the simulations show the effectiveness of the proposed designs in improving system performance, and confirm their superiority to existing works. Moreover, their feasibility in general SM-MIMO systems is verified as well. Furthermore, the proposed designs can indeed outperform other existing works.

碩士
國立中山大學
通訊工程研究所
103
The generalized spatial modulation (GSM) is developed as a promising modulation scheme which effectively compromises the hardware complexity and the spectral efficiency in the multiple-input and multiple-output (MIMO) systems. In this paper, we further propose a precoding design for improving the performance of GSM-MIMO systems. We first formulate precoding design as an optimization of which the worst-case minimum free-distance can be maximized. As well know, the free-distance is the critical metric in evaluating the performance of the maximum likelihood (ML) detection. To facilitate the derivation, we then decompose the precoder design into the power allocation times a structured precoder for each antenna group. With the decomposition, we can easily derive a closed-form solution for the precoder design, which can greatly reduce the computational complexity and is suitable for the real-time implementation. Simulation results show the superiority of our design measured by both the BER and computational complexity compared with the existing methods.

碩士
國立暨南國際大學
電機工程學系
104
Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique. Since its high-speed transmission and robustness against frequency selective channel fading, it is widely adopted in modern wireless communications. However, high peak-to-average power ratio (PAPR) is disadvantage of OFDM. This leads to design problem of power amplifier. In the physical-layer of long Term Evolution (LTE), single-carrier is used for the uplink transmission, and this efficiently lessens the effect of high PAPR. In this thesis, we propose a frequency domain equalization technique for the single-carrier spatial modulation based multiple-input multiple-output system. We employ matrix inverse lemma for sub-block matrices to reduce the computational complexity of the involved matrix inverse in the minimum mean-squared error detection. Also, we apply the M-algorithm for use with the maximum-likelihood approach for selecting the candidates of decision. Results show that better error-rate performance can be obtained.

Multi-antenna wireless systems have become very popular due to their theoretically predicted higher spectral efficiencies and improved performance compared to single-antenna systems. Large-scale multiple-input multiple-output (MIMO) systems refer to wireless systems where communication terminals employ tens to hundreds of antennas to achieve in-creased spectral efficiencies/sum rates, reliability, and power efficiency. Large-scale multi-antenna systems are attractive to meet the increasing wireless data rate requirements, without compromising on the bandwidth. This thesis addresses key signal processing issues in large-scale MIMO systems. Specifically, the thesis investigates efficient algorithms for signal detection and channel estimation in large-scale MIMO systems. It also investigates ‘spatial modulation,’ a multi-antenna modulation scheme that can reduce the number of transmit radio frequency (RF) chains, without compromising much on the spectral efficiency. The work reported in this thesis is comprised of the following two parts: 1 investigation of low-complexity receiver algorithms based on Markov chain Monte Carlo (MCMC) technique, tabu search, and belief propagation for large-scale uplink multiuser MIMO systems, and 2 investigation of achievable rates and signal detection in generalized spatial modulation. 1. Receiver algorithms for large-scale multiuser MIMO systems on the uplink In this part of the thesis, we propose low-complexity algorithms based on MCMC techniques, Gaussian sampling based lattice decoding (GSLD), reactive tabu search (RTS), and factor graph based belief propagation (BP) for signal detection on the uplink in large-scale multiuser MIMO systems. We also propose an efficient channel estimation scheme based on Gaussian sampling. Markov chain Monte Carlo (MCMC) sampling: We propose a novel MCMC based detection algorithm, which achieves near-optimal performance in large dimensions at low complexities by the joint use of a mixed Gibbs sampling (MGS) strategy and a multiple restart strategy with an efficient restart criterion. The proposed mixed Gibbs sampling distribution is a weighted mixture of the target distribution and uniform distribution. The presence of the uniform component in the sampling distribution allows the algorithm to exit from local traps quickly and alleviate the stalling problem encountered in conventional Gibbs sampling. We present an analysis for the optimum choice of the mixing ratio. The analysis approach is to define an absorbing Markov chain and use its property regarding the expected number of iterations needed to reach the global minima for the first time. We also propose an MCMC based algorithm which exploits the sparsity in uplink multiuser MIMO transmissions, where not all users are active simultaneously. Gaussian sampling based lattice decoding: Next, we investigate the problem of searching the closest lattice point in large dimensional lattices and its use in signal detection in large-scale MIMO systems. Specifically, we propose a Gaussian sampling based lattice decoding (GSLD) algorithm. The novelty of this algorithm is that, instead of sampling from a discrete distribution as in Gibbs sampling, the algorithm iteratively generates samples from a continuous Gaussian distribution, whose parameters are obtained analytically. This makes the complexity of the proposed algorithm to be independent of the size of the modulation alpha-bet. Also, the algorithm is able to achieve near-optimal performance for different antenna and modulation alphabet settings at low complexities. Random restart reactive tabu search (R3TS): Next, we study receiver algorithms based on reactive tabu search (RTS) technique in large-scale MIMO systems. We propose a multiple random restarts based reactive tabu search (R3TS) algorithm that achieves near-optimal performance in large-scale MIMO systems. A key feature of the proposed R3TS algorithm is its performance based restart criterion, which gives very good performance-complexity tradeoff in large-dimension systems. Lower bound on maximum likelihood (ML) bit error rate (BER) performance: We propose an approach to obtain lower bounds on the ML performance of large-scale MIMO systems using RTS simulation. In the proposed approach, we run the RTS algorithm using the transmitted vector as the initial vector, along with a suitable neighborhood definition, and find a lower bound on number of errors in ML solution. We demonstrate that the proposed bound is tight (within about 0.5 dB of the optimal performance in a 16×16MIMO system) at moderate to high SNRs. Factor graph using Gaussian approximation of interference (FG-GAI): Multiuser MIMO channels can be represented by graphical models that are fully/densely connected (loopy graphs), where conventional belief propagation yields suboptimal performance and requires high complexity. We propose a solution to this problem that uses a simple, yet effective, Gaussian approximation of interference (GAI) approach that carries out a linear per-symbol complexity message passing on a factor graph (FG) based graphical model. The proposed algorithm achieves near-optimal performance in large dimensions in frequency-flat as well as frequency-selective channels. Gaussian sampling based channel estimation: Next, we propose a Gaussian sampling based channel estimation technique for large-scale time-division duplex (TDD) MIMO systems. The proposed algorithm refines the initial estimate of the channel by iteratively detecting the data block and using that knowledge to improve the estimated channel knowledge using a Gaussian sampling based technique. We demonstrate that this algorithm achieves near-optimal performance both in terms of mean square error of the channel estimates and BER of detected data in both frequency-flat and frequency-selective channels. 2. Generalized spatial modulation In the second part of the thesis, we investigate generalized spatial modulation (GSM) in point-to point MIMO systems. GSM is attractive because of its ability to work with less number of transmit RF chains compared to traditional spatial multiplexing, without com-promising much on spectral efficiency. In this work, we show that, by using an optimum combination of number of transmit antennas and number of transmit RF chains, GSM can achieve better throughput and/or BER than spatial multiplexing. We compute tight bounds on the maximum achievable rate in a GSM system, and quantify the percentage savings in the number of transmit RF chains as well as the percentage increase in the rate achieved in GSM compared to spatial multiplexing. We also propose a Gibbs sampling based algorithm suited to detect GSM signals, which yields impressive BER performance and complexity results.

Multi-antenna wireless systems have become very popular due to their theoretically predicted higher spectral efficiencies and improved performance compared to single-antenna systems. Large-scale multiple-input multiple-output (MIMO) systems refer to wireless systems where communication terminals employ tens to hundreds of antennas to achieve in-creased spectral efficiencies/sum rates, reliability, and power efficiency. Large-scale multi-antenna systems are attractive to meet the increasing wireless data rate requirements, without compromising on the bandwidth. This thesis addresses key signal processing issues in large-scale MIMO systems. Specifically, the thesis investigates efficient algorithms for signal detection and channel estimation in large-scale MIMO systems. It also investigates ‘spatial modulation,’ a multi-antenna modulation scheme that can reduce the number of transmit radio frequency (RF) chains, without compromising much on the spectral efficiency. The work reported in this thesis is comprised of the following two parts: 1 investigation of low-complexity receiver algorithms based on Markov chain Monte Carlo (MCMC) technique, tabu search, and belief propagation for large-scale uplink multiuser MIMO systems, and 2 investigation of achievable rates and signal detection in generalized spatial modulation. 1. Receiver algorithms for large-scale multiuser MIMO systems on the uplink In this part of the thesis, we propose low-complexity algorithms based on MCMC techniques, Gaussian sampling based lattice decoding (GSLD), reactive tabu search (RTS), and factor graph based belief propagation (BP) for signal detection on the uplink in large-scale multiuser MIMO systems. We also propose an efficient channel estimation scheme based on Gaussian sampling. Markov chain Monte Carlo (MCMC) sampling: We propose a novel MCMC based detection algorithm, which achieves near-optimal performance in large dimensions at low complexities by the joint use of a mixed Gibbs sampling (MGS) strategy and a multiple restart strategy with an efficient restart criterion. The proposed mixed Gibbs sampling distribution is a weighted mixture of the target distribution and uniform distribution. The presence of the uniform component in the sampling distribution allows the algorithm to exit from local traps quickly and alleviate the stalling problem encountered in conventional Gibbs sampling. We present an analysis for the optimum choice of the mixing ratio. The analysis approach is to define an absorbing Markov chain and use its property regarding the expected number of iterations needed to reach the global minima for the first time. We also propose an MCMC based algorithm which exploits the sparsity in uplink multiuser MIMO transmissions, where not all users are active simultaneously. Gaussian sampling based lattice decoding: Next, we investigate the problem of searching the closest lattice point in large dimensional lattices and its use in signal detection in large-scale MIMO systems. Specifically, we propose a Gaussian sampling based lattice decoding (GSLD) algorithm. The novelty of this algorithm is that, instead of sampling from a discrete distribution as in Gibbs sampling, the algorithm iteratively generates samples from a continuous Gaussian distribution, whose parameters are obtained analytically. This makes the complexity of the proposed algorithm to be independent of the size of the modulation alpha-bet. Also, the algorithm is able to achieve near-optimal performance for different antenna and modulation alphabet settings at low complexities. Random restart reactive tabu search (R3TS): Next, we study receiver algorithms based on reactive tabu search (RTS) technique in large-scale MIMO systems. We propose a multiple random restarts based reactive tabu search (R3TS) algorithm that achieves near-optimal performance in large-scale MIMO systems. A key feature of the proposed R3TS algorithm is its performance based restart criterion, which gives very good performance-complexity tradeoff in large-dimension systems. Lower bound on maximum likelihood (ML) bit error rate (BER) performance: We propose an approach to obtain lower bounds on the ML performance of large-scale MIMO systems using RTS simulation. In the proposed approach, we run the RTS algorithm using the transmitted vector as the initial vector, along with a suitable neighborhood definition, and find a lower bound on number of errors in ML solution. We demonstrate that the proposed bound is tight (within about 0.5 dB of the optimal performance in a 16×16MIMO system) at moderate to high SNRs. Factor graph using Gaussian approximation of interference (FG-GAI): Multiuser MIMO channels can be represented by graphical models that are fully/densely connected (loopy graphs), where conventional belief propagation yields suboptimal performance and requires high complexity. We propose a solution to this problem that uses a simple, yet effective, Gaussian approximation of interference (GAI) approach that carries out a linear per-symbol complexity message passing on a factor graph (FG) based graphical model. The proposed algorithm achieves near-optimal performance in large dimensions in frequency-flat as well as frequency-selective channels. Gaussian sampling based channel estimation: Next, we propose a Gaussian sampling based channel estimation technique for large-scale time-division duplex (TDD) MIMO systems. The proposed algorithm refines the initial estimate of the channel by iteratively detecting the data block and using that knowledge to improve the estimated channel knowledge using a Gaussian sampling based technique. We demonstrate that this algorithm achieves near-optimal performance both in terms of mean square error of the channel estimates and BER of detected data in both frequency-flat and frequency-selective channels. 2. Generalized spatial modulation In the second part of the thesis, we investigate generalized spatial modulation (GSM) in point-to point MIMO systems. GSM is attractive because of its ability to work with less number of transmit RF chains compared to traditional spatial multiplexing, without com-promising much on spectral efficiency. In this work, we show that, by using an optimum combination of number of transmit antennas and number of transmit RF chains, GSM can achieve better throughput and/or BER than spatial multiplexing. We compute tight bounds on the maximum achievable rate in a GSM system, and quantify the percentage savings in the number of transmit RF chains as well as the percentage increase in the rate achieved in GSM compared to spatial multiplexing. We also propose a Gibbs sampling based algorithm suited to detect GSM signals, which yields impressive BER performance and complexity results.

碩士
國立臺灣科技大學
電機工程系
107
Spatial Modulation(SM) is one of the most adopted Multiple-Input Multiple-Output(MIMO) techniques in recent years. Its characteristics are only activating one single antenna at the same time, antenna index and transmitted symbol and both being used by the transmission bit. The intention is to increase the spectral efficiency and energy efficiency, there are many other MIMO techniques have been proposed based on the same concept, such as Generalized Spatial Modulation(GSM), Space Shift Keying(SSK), Space Time Shift Keying(STSK) and so on. Generalized Spatial Modulation is an extended version of Spatial Modulation, it activated more than one antenna at the same time, using number of combinations of different antennas, which makes the antenna number no longer has to be limited by the power of two. Generalized Spatial Modulation has more flexibility than original Spatial Modulation. In this thesis, we adopt Orthogonal Frequency Division Multiplexing(OFDM) which is widely used in wireless communication systems and Single Carrier Frequency Division Multiple Access(SC-FDMA) proposed by LTE-A, which adopt Discrete Fourier Transform (DFT) as a precoding scheme and known for its low Peak to Average Power Ratio (PAPR) characteristic as the uplink system. We combine these two systems with GSM, in order to have better bit error rate(BER) and spectral efficiency. In this thesis, we discussed combinations of Spatial Modulation with OFDM and SC-FDMA and proposed GSM-OFDM and GSM-SCFDMA. We will simulate all the systems BER performance in different number antenna case and modulation type through different channel model. Also we discussed the PAPR performance after adding SM and GSM.

Considerando os avanços tecnológicos das últimas décadas, espera-se que a próxima geração de comunicações sem fios siga a tendência de um aumento significativo da robustez do sistema, da eficiência espectral (SE) e da eficiência energética (EE). Atualmente na era do pós-5G, os esquemas de "Multiple Input, Multiple Output" (MIMO) baseados em modulações espaciais generalizadas (GSM) bem como noutras modulações de índices (IM), têm sido amplamente considerados como potenciais técnicas candidatas para as redes sem fios. Esta dissertação tem como objetivo desenhar e estudar um sistema MIMO para comunicações multiutilizador integrando símbolos GSM e símbolos de modulação de índices generalizada no espaço-frequência (GSFIM). Numa primeira parte estuda-se um sistema MIMO multiutilizador, em que uma estação base (BS) transmite símbolos GSM pré-codificados para vários recetores. Na abordagem GSM adotada, múltiplas antenas transmitem simultaneamente diferentes símbolos M-QAM de alto nível, até M =1024. O pré-codificador é desenvolvido de modo a remover interferências entre utilizadores enquanto um algoritmo iterativo baseado no "alternating direction method of multipliers" (ADMM) é aplicado no recetor para realizar a deteção GSM de um único utilizador. Os resultados mostram que a abordagem GSM MU-MIMO apresentada é capaz de explorar eficazmente um grande número de antenas de transmissão implantadas no transmissor e também proporcionar ganhos de desempenho sobre esquemas convencionais MU-MIMO com eficiências espectrais idênticas. Numa segunda parte, introduz-se uma nova dimensão (para além do espaço), a frequência. Estuda-se assim o comportamento dos recetores MMSE e OB-MMSE, num sistema MIMO baseado em GSFIM. Os resultados mostram que o sistema GSFIM MUMIMO explora de forma competente as comunicações com grande número de antenas/sub-portadoras, apresentando melhores desempenhos quando usada com um recetor OB-MMSE.
Considering the technological advances of the last decades, the next generation of wireless communications is expected to follow the trend of a significant increase in system robustness, spectral efficiency (SE) and energy efficiency (EE). Today in the post5G era, Multiple Input, Multiple Output (MIMO) schemes based on generalised spatial modulations (GSM) as well as other index modulations (IM) have been widely considered as potential candidate techniques for wireless networks. This dissertation aims to design and study a MIMO system for multi-user communications integrating GSM symbols and generalised space-frequency index modulation (GSFIM) symbols. In a first part, a multi-user MIMO system is studied, in which a base station (BS) transmits pre-coded GSM symbols to several receivers. In the GSM approach adopted, multiple antennas transmit different high-level M-QAM symbols simultaneously, up to M =1024. The precoder is designed to remove interference between users while an iterative algorithm based on the alternating direction method of multipliers (ADMM) is applied to the receiver to perform single user GSM detection. The results show that the GSM MU-MIMO approach presented is capable of effectively exploiting a large number of transmission antennas deployed on the transmitter and also provides desempenho gains over conventional MU-MIMO schemes with identical spectral efficiencies. In a second part, a new dimension (beyond space) is introduced, frequency. The behaviour of MMSE and OB-MMSE receivers in a GSFIM-based MIMO system is thus studied. The results show that the GSFIM MU-MIMO system competently exploits communications with large numbers of antennas/sub-carriers and performs better when used with an OB-MMSE receiver.

This work consists of two main parts: i) Design and implementation of a compact current-reusing 2.4GHz direct-modulation transmitter with on-chip automatic tuning; ii) Design and implementation of a novel highly-reconfigurable, continuously tunable, power-adjustable Active-RC filter for multiple standards. The design, analysis, and experimental verification of a proposed self-calibrating, current reused 2.4GHz, direct-modulation transmitter are introduced. A stacked arrangement of the power amplifier/voltage-controlled oscillator is presented along with a novel LC-tank-tuning algorithm with a simple, low-cost, on-chip implementation. To transmit maximum power, the tuning loop ensures the PA's resonant tank is centered around the operating frequency, and the loop requires no ADC, DSP, or external signal generator. This work also details the proposed tuning-loop algorithm and examines the frequency-dependent nonlinear power-detector. The system was implemented in TSMC 0.18[mu]m CMOS, occupies 0.7 mm² (TX) + 0.1 mm² (self tuning), and was measured in a QFN48 package on FR4 PCB. Automatically adjusting the tank-tuning bits within their tuning range results in >4dB increase in output power. With the self-tuning circuit active, the transmitter delivers a measured output power of > 0dBm to a 100-[omega] differential load, and the system consumes 22.9 mA from a 2.2-V supply. A biquad design methodology and a baseband low-pass filter is presented for wireless and wireline applications with reconfigurable frequency response, selectable order (1st/3rd/5th), continuously tunable cutoff frequency (1MHz-20MHz) and adjustable power consumption (3mW-7.5mW). A discrete capacitor array coarsely tunes the low-pass filter, and a novel Continuous Impedance Multiplier (CIM) then finely tunes the filter. Resistive/capacitive networks select between the Chebyshev and Inverse Chebyshev approximation types. Also, a new stability metric for biquads, Minimum Acceptable Phase Margin (MAPM), is presented and discussed in the context of filter compensation and passband ripple considerations. Experimental results yield an IIP3 of 31.3dBm, a THD of -40dB at 447mV[subscript pk, diff] input signal amplitude, and a DR of 71.4dB. The filters tunable range covers frequencies from 1MHz to 20MHz. In Inverse Chebyshev mode, the filter achieves a passband group delay variation less than ±2:5%. The design is fabricated in 0.13[mu]m CMOS, occupies 1.53mm², and operates from a 1-V supply.

Multi-antenna wireless communication systems that employ a large number of antennas have recently stirred a lot of research interest. This is mainly due to the possibility of achieving very high spectral efficiency, power efficiency, and link reliability in such large-scale multiple-input multiple-output (MIMO) systems. An emerging architecture for large-scale multiuser MIMO communications is one where each base station (BS) is equipped with a large number of antennas (tens to hundreds of antennas) and the user terminals are equipped with fewer antennas (one to four antennas) each. The backhaul communication between base stations is also carried out using large number of antennas. Because of the high dimensionality of large-scale MIMO signals, the computational complexity of various transceiver operations can be prohibitively large. Therefore, low complexity techniques that scale well for transceiver signal processing in such large-scale MIMO systems are crucial. The transceiver operations of interest include signal encoding at the transmitter, and channel estimation, detection and decoding at the receiver. This thesis focuses on the design and analysis of novel low-complexity transceiver signal processing schemes for large-scale MIMO systems. In this thesis, we consider two types of large-scale MIMO systems, namely, massive MIMO systems and generalized spatial modulation MIMO (GSM-MIMO) systems. In massive MIMO, the mapping of information bits to modulation symbols is done using conventional modulation alphabets (e.g., QAM, PSK). In GSM-MIMO, few of the avail-able transmit antennas are activated in a given channel use, and information bits are conveyed through the indices of these active antennas, in addition to the bits conveyed through conventional modulation symbols. We also propose a novel modulation scheme named as precoder index modulation, where information bits are conveyed through the index of the chosen precoder matrix as well as the modulation symbols transmitted. Massive MIMO: In this part of the thesis, we propose a novel MIMO receiver which exploits channel hardening that occurs in large-scale MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of HH H become much weaker compared to the diagonal terms as the size of the channel gain matrix H increases. We exploit this phenomenon to devise a low-complexity channel estimation scheme and a message passing algorithm for signal detection at the BS receiver in massive MIMO systems. We refer to the proposed receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The key novelties in the proposed CHEMP receiver are: (i) operation on the matched filtered system model, (ii) Gaussian approximation on the off-diagonal terms of the HH H matrix, and (iii) direct estimation of HH H instead of H and use of this estimate of HH H for detection The performance and complexity results show that the proposed CHEMP receiver achieves near-optimal performance in large-scale MIMO systems at complexities less than those of linear receivers like minimum mean squared error (MMSE) receiver. We also present a log-likelihood ratio (LLR) analysis that provides an analytical reasoning for this better performance of the CHEMP receiver. Further, the proposed message passing based detection algorithm enables us to combine it with low density parity check (LDPC) decoder to formulate a joint message passing based detector-decoder. For this joint detector-decoder, we design optimized irregular binary LDPC codes specific to the massive MIMO channel and the proposed receiver through EXIT chart matching. The LDPC codes thus obtained are shown to achieve improved coded bit error rate (BER) performance compared to off-the-shelf irregular LDPC codes. The performance of the CHEMP receiver degrades when the system loading factor (ratio of the number of users to the number of BS antennas) and the modulation alpha-bet size are large. It is of interest to devise receiver algorithms that work well for high system loading factors and modulation alphabet sizes. For this purpose, we propose a low-complexity factor-graph based vector message passing algorithm for signal detection. This algorithm uses a scalar Gaussian approximation of interference on the basic sys-tem model. The performance results show that this algorithm performs well for large modulation alphabets and high loading factors. We combine this detection algorithm with a non-binary LDPC decoder to obtain a joint detector-decoder, where the field size of the non-binary LDPC code is same as the size of the modulation alphabet. For this joint message passing based detector-decoder, we design optimized non-binary irregular LDPC codes tailored to the massive MIMO channel and the proposed detector. GSM-MIMO: In this part of the thesis, we consider GSM-MIMO systems in point-to-point as well as multiuser communication settings. GSM-MIMO has the advantage of requiring only fewer transmit radio frequency (RF) chains than the number of transmit antennas. We analyze the capacity of point-to-point GSM-MIMO, and obtain lower and upper bounds on the GSM-MIMO system capacity. We also derive an upper bound on the BER performance of maximum likelihood detection in GSM-MIMO systems. This bound is shown to be tight at moderate to high signal-to-noise ratios. When the number of transmit and receive antennas are large, the complexity of en-coding and decoding of GSM-MIMO signals can be prohibitively high. To alleviate this problem, we propose a low complexity GSM-MIMO encoding technique that utilizes com-binatorial number system for bits-to-symbol mapping. We also propose a novel layered message passing (LaMP) algorithm for decoding GSM-MIMO signals. Low computational complexity is achieved in the LaMP algorithm by detecting the modulation bits and the antenna index bits in two deferent layers. We then consider large-scale multiuser GSM-MIMO systems, where multiple users employ GSM at their transmitters to communicate with a BS having a large number of receive antennas. For this system, we develop computationally efficient message passing algorithms for signal detection using vector Gaussian approximation of interference. The performance results of these algorithms show that the GSM-MIMO system outperforms the massive MIMO system by several dBs for the same spectral efficiency. Precoder index modulation: It is known that the performance of a communication link can be enhanced by exploiting time diversity without reducing the rate of transmission using pseudo random phase preceding (PRPP). In order to further improve the performance of GSM-MIMO, we apply PRPP technique to GSM-MIMO systems. PRPP provides additional diversity advantage at the receiver and further improves the performance of GSM-MIMO systems. For PRPP-GSM systems, we propose methods to simultaneously precode both the antenna index bits and the modulation symbols using rectangular precoder matrices. Finally, we extend the idea of index modulation to pre-coding and propose a new modulation scheme referred to as precoder index modulation (PIM). In PIM, information bits are conveyed through the index of a prehared PRPP matrix, in addition to the information bits conveyed through the modulation symbols. PIM is shown to increase the achieved spectral efficiency, in addition to providing diver-sity advantages.

Multi-antenna wireless communication systems that employ a large number of antennas have recently stirred a lot of research interest. This is mainly due to the possibility of achieving very high spectral efficiency, power efficiency, and link reliability in such large-scale multiple-input multiple-output (MIMO) systems. An emerging architecture for large-scale multiuser MIMO communications is one where each base station (BS) is equipped with a large number of antennas (tens to hundreds of antennas) and the user terminals are equipped with fewer antennas (one to four antennas) each. The backhaul communication between base stations is also carried out using large number of antennas. Because of the high dimensionality of large-scale MIMO signals, the computational complexity of various transceiver operations can be prohibitively large. Therefore, low complexity techniques that scale well for transceiver signal processing in such large-scale MIMO systems are crucial. The transceiver operations of interest include signal encoding at the transmitter, and channel estimation, detection and decoding at the receiver. This thesis focuses on the design and analysis of novel low-complexity transceiver signal processing schemes for large-scale MIMO systems. In this thesis, we consider two types of large-scale MIMO systems, namely, massive MIMO systems and generalized spatial modulation MIMO (GSM-MIMO) systems. In massive MIMO, the mapping of information bits to modulation symbols is done using conventional modulation alphabets (e.g., QAM, PSK). In GSM-MIMO, few of the avail-able transmit antennas are activated in a given channel use, and information bits are conveyed through the indices of these active antennas, in addition to the bits conveyed through conventional modulation symbols. We also propose a novel modulation scheme named as precoder index modulation, where information bits are conveyed through the index of the chosen precoder matrix as well as the modulation symbols transmitted. Massive MIMO: In this part of the thesis, we propose a novel MIMO receiver which exploits channel hardening that occurs in large-scale MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of HH H become much weaker compared to the diagonal terms as the size of the channel gain matrix H increases. We exploit this phenomenon to devise a low-complexity channel estimation scheme and a message passing algorithm for signal detection at the BS receiver in massive MIMO systems. We refer to the proposed receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The key novelties in the proposed CHEMP receiver are: (i) operation on the matched filtered system model, (ii) Gaussian approximation on the off-diagonal terms of the HH H matrix, and (iii) direct estimation of HH H instead of H and use of this estimate of HH H for detection The performance and complexity results show that the proposed CHEMP receiver achieves near-optimal performance in large-scale MIMO systems at complexities less than those of linear receivers like minimum mean squared error (MMSE) receiver. We also present a log-likelihood ratio (LLR) analysis that provides an analytical reasoning for this better performance of the CHEMP receiver. Further, the proposed message passing based detection algorithm enables us to combine it with low density parity check (LDPC) decoder to formulate a joint message passing based detector-decoder. For this joint detector-decoder, we design optimized irregular binary LDPC codes specific to the massive MIMO channel and the proposed receiver through EXIT chart matching. The LDPC codes thus obtained are shown to achieve improved coded bit error rate (BER) performance compared to off-the-shelf irregular LDPC codes. The performance of the CHEMP receiver degrades when the system loading factor (ratio of the number of users to the number of BS antennas) and the modulation alpha-bet size are large. It is of interest to devise receiver algorithms that work well for high system loading factors and modulation alphabet sizes. For this purpose, we propose a low-complexity factor-graph based vector message passing algorithm for signal detection. This algorithm uses a scalar Gaussian approximation of interference on the basic sys-tem model. The performance results show that this algorithm performs well for large modulation alphabets and high loading factors. We combine this detection algorithm with a non-binary LDPC decoder to obtain a joint detector-decoder, where the field size of the non-binary LDPC code is same as the size of the modulation alphabet. For this joint message passing based detector-decoder, we design optimized non-binary irregular LDPC codes tailored to the massive MIMO channel and the proposed detector. GSM-MIMO: In this part of the thesis, we consider GSM-MIMO systems in point-to-point as well as multiuser communication settings. GSM-MIMO has the advantage of requiring only fewer transmit radio frequency (RF) chains than the number of transmit antennas. We analyze the capacity of point-to-point GSM-MIMO, and obtain lower and upper bounds on the GSM-MIMO system capacity. We also derive an upper bound on the BER performance of maximum likelihood detection in GSM-MIMO systems. This bound is shown to be tight at moderate to high signal-to-noise ratios. When the number of transmit and receive antennas are large, the complexity of en-coding and decoding of GSM-MIMO signals can be prohibitively high. To alleviate this problem, we propose a low complexity GSM-MIMO encoding technique that utilizes com-binatorial number system for bits-to-symbol mapping. We also propose a novel layered message passing (LaMP) algorithm for decoding GSM-MIMO signals. Low computational complexity is achieved in the LaMP algorithm by detecting the modulation bits and the antenna index bits in two deferent layers. We then consider large-scale multiuser GSM-MIMO systems, where multiple users employ GSM at their transmitters to communicate with a BS having a large number of receive antennas. For this system, we develop computationally efficient message passing algorithms for signal detection using vector Gaussian approximation of interference. The performance results of these algorithms show that the GSM-MIMO system outperforms the massive MIMO system by several dBs for the same spectral efficiency. Precoder index modulation: It is known that the performance of a communication link can be enhanced by exploiting time diversity without reducing the rate of transmission using pseudo random phase preceding (PRPP). In order to further improve the performance of GSM-MIMO, we apply PRPP technique to GSM-MIMO systems. PRPP provides additional diversity advantage at the receiver and further improves the performance of GSM-MIMO systems. For PRPP-GSM systems, we propose methods to simultaneously precode both the antenna index bits and the modulation symbols using rectangular precoder matrices. Finally, we extend the idea of index modulation to pre-coding and propose a new modulation scheme referred to as precoder index modulation (PIM). In PIM, information bits are conveyed through the index of a prehared PRPP matrix, in addition to the information bits conveyed through the modulation symbols. PIM is shown to increase the achieved spectral efficiency, in addition to providing diver-sity advantages.

Devido à necessidade de atender aos requisitos associados ao mercado móvel cada vez mais exigente, a quinta geração (5G) de comunicações sem fio é caracterizada por proporcionar alta eficiência espectral (SE) e elevada eficiência energética (EE). Neste enquadramento, surgem tecnologias fundamentais para redes de próxima geração, como os sistemas massivos com múltiplas entradas e múltiplas saídas (M-MIMO) baseados em modulação espacial generalizada (GSM), a qual constitui um caso específico de modulação de índices (IM). Nestes sistemas, torna-se possível a utilização de ondas milimétricas (mmWave), as quais permitem providenciar taxas de dados mais elevadas, embora introduzam limitações na cobertura, devido ao aumento da atenuação do sinal. Com o intuito de avaliar o desempenho da comunicação milimétrica em sistemas 5G, efetuou-se o desenvolvimento e atualização de um simulador a nível de sistema, de forma a simular uma rede 5G New Radio (NR), incluindo a implementação de três cenários tridimensionais distintos (UMa, UMi - Street canyon e InO), aplicando diferentes modulações e a mesma numerologia e faixa de frequência. Numa segunda etapa, procedeu-se à análise e discussão dos resultados obtidos, derivados das diversas simulações elaboradas, tanto a nível de "throughput", em função do número de utilizadores e do número de antenas TRP ativas, como a nível de cobertura. Assim, os resultados indicam que os cenários "outdoor", particularmente o cenário UMa, apresentam melhor desempenho e, a nível de "throughput", a modulação 64QAM permite alcançar resultados mais elevados, enquanto que, a nível de cobertura, a modulação QPSK apresenta a melhor performance.
Due to the need to meet the requirements of the increasingly demanding mobile market, the fifth generation (5G) of wireless communications is characterized by providing high spectral efficiency (SE) and high energy efficiency (EE). Therefore, there are emerging fundamental technologies used for the next generation networks, such as massive multiple-input multiple-output systems (M-MIMO) based on generalized spatial modulation (GSM), which constitutes a particular case of index modulation (IM). In these systems, it is possible to use millimeter waves (mmWave), which provide extreme data rates, although limitations in coverage are introduced due to the increased signal attenuation. With the purpose of evaluate the performance of millimeter wave communication in 5G systems, a system-level simulator was developed and updated, in order to simulate a 5G New Radio (NR) network, where three different three-dimensional scenarios (UMa, UMi – Street canyon and InO) were employed, using different modulations and the same numerology and frequency range. In a second phase, the results obtained from the system level simulations were analysed and discussed, both in terms of throughput, depending on the number of users and the number of active TRP antennas, and in terms of coverage. Consequently, the results indicate that outdoor scenarios, particularly the UMa scenario, can achieve an improved performance and, in terms of throughput, 64QAM modulation is able to obtain superior results, while, in terms of coverage, QPSK modulation presents the best performance.