Dissertations / Theses on the topic 'Generalised Spatial Modulation'

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA<br>Spatial modulation (SM) is a transmission scheme where only one transmit antenna is active at any time instant. It thus reduces interchannel interference (ICI) and receiver complexity over traditional multi-antenna systems. However, the spectral efficiency of SM is low. To improve the spectral efficiency, generalized spatial modulation (GSM) can be used. In this paper, we propose to apply the Alamouti technique with GSM for correlated antennas, and show that the proposed approach provides significant improvement over conventional SM and GSM. Our study also shows the importance of bit-to-antenna mappings and their roles on the selection of appropriate correlated antennas.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV<br>Spatial modulation (SM) reduces transceiver complexity and inter-channel interference over traditional multiple input multiple output (MIMO) systems. It has been shown recently in the literature that the use of a precoder in an SM or a generalized spatial modulation (GSM) system can significantly improve error performance. This paper investigates two issues related to precoders: 1) the use of a precoder in Alamouti-GSM systems, and 2) the effects of power constraints on the precoder design. The results in this paper show that Alamouti-GSM can improve system performance by several dB. On power constraint issues, the paper shows that there is a trade-off between limiting antenna power fluctuations and the potential gain due to precoders.

The present study analyses three beam shaping approaches with respect to a light-efficient generation of i) patterns and ii) multiple spots by means of a generic optical 4f-setup. 4f approaches share the property that due to the one-to-one relationship between output intensity and input phase, the need for time-consuming, iterative calculation can be avoided. The resulting low computational complexity offers a particular advantage compared to the widely used holographic principles and makes them potential candidates for real-time applications. The increasing availability of high-speed phase modulators, e.g. on the basis of MEMS, calls for an evaluation of the performances of these concepts. Our second interest is the applicability of 4f methods to high-power applications. We discuss the variants of 4f intensity shaping by phase modulation from a system-level point of view which requires the consideration of application relevant boundary conditions. The discussion includes i) the micro mirror based phase manipulation combined with amplitude masking in the Fourier plane, ii) the Generalized Phase Contrast, and iii) matched phase-only correlation filtering combined with GPC. The conceptual comparison relies on comparative figures of merit for energy efficiency, pattern homogeneity, pattern image quality, maximum output intensity and flexibility with respect to the displayable pattern. Numerical simulations illustrate our findings.

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.

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.<br>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.

碩士<br>國立中山大學<br>通訊工程研究所<br>106<br>Spatial-Multiplexing aided Generalized Spatial Modulation (SMx-GSM) is essentially a combination of Vertical Bell Labs Layered Space-Time and Generalized Spatial Modulation (GSM) to achieve a high transmission rate technology. In transmitter, the transmit antennas are divided into several groups and each group use GSM technique. Therefore, we don’t need a lot of Radio Frequency chain to transmit signal and will not cause serious inter-channel interference. Compare to the conventional GSM, we can implement high transmission rate system by using the characteristics of SMx-GSM symbols at receiver. In this thesis, we explain a low-complexity detector for SMx-GSM. We use tree search algorithm and utilize a low-complexity cost function to find a set of transmit antenna combinations with maximum a posteriori probability for optimal detection. From the results of the simulation, the detection complexity can be greatly reduced, that make high-rate system feasible.

Traditionally, symbols chosen from complex modulation alphabets such as QAM and PSK are used to convey information bits, and complex fades introduced by the channel are viewed as detrimental effects that cause amplitude and phase distortion to the transmitted symbols. An alternative and interesting approach is to consider the complex channel fade coefficients themselves to constitute a modulation alphabet (referred to as `channel alphabet'). An example of this approach is a recently proposed `media-based modulation (MBM)' scheme, which uses digitally controllable parasitic elements (called as radio frequency mirrors) near the transmit antenna(s) to create the channel alphabet. Each radio frequency (RF) mirror can be either ON or OFF. A mirror allows the incident RF signal to pass through it transparently when it is ON, and reflects back the incident RF signal when it is OFF. The ON/OFF status of the mirrors is called as `mirror activation pattern (MAP)'. The channel alphabet needs to be known only at the receiver and not at the transmitter. MBM has been shown to achieve significant performance gains compared to conventional modulation schemes. In this thesis, we investigate the performance of MBM in various scenarios like transmission with feedback, differential transmission, imperfect channel state information, full-duplex communications, and cooperative relaying. The contributions in this thesis are three-fold. In the first part, we investigate the performance of some interesting physical layer techniques when applied to MBM. First, we combine MBM with generalized spatial modulation (GSM), and investigate its performance. Next, we study the performance of feedback based mirror activation pattern (MAP) selection (analogous to transmit antenna selection in multi-antenna systems), and phase compensation and constellation rotation (PC-CR) techniques in MBM. We also analyze the diversity orders achieved by the ED-based MAP selection scheme and the PC-CR scheme. In the second part, we deal with channel estimation aspects in MBM. First, we present a differential MBM (DMBM) scheme which does not require estimation of channel modulation alphabet at the receiver for detection. We also propose a low-complexity maximum-likelihood (ML) detection algorithm for DMBM. Next, we analyze the effect of imperfect channel estimation on the bit error performance of MBM. We analyze the performance for two types of detectors, namely, i) the commonly studied mismatched detector, and ii) the true ML detector that maximizes the likelihood by taking the statistics of the channel estimate into account. In the final part, we investigate the performance of full-duplex (FD) communication using MBM, and compare it with that of FD with conventional modulation schemes. First, we investigate the FD communication using MBM and DMBM in a point-to-point setting, and present detectors for signal detection. Next, we analyze the performance of a two-hop three-node FD relay network, where the source and relay nodes transmit using MBM. The relay uses decode-and-forward (DF) relaying protocol. Next, we investigate the performance of MBM in a two-way relaying network, where two FD nodes exchange information with the help of a FD relay node using DF protocol.

碩士<br>國立中山大學<br>通訊工程研究所<br>103<br>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<br>國立清華大學<br>通訊工程研究所<br>103<br>The concept of Generalized Spatial modulation (GSM) has been proposed as a promising architecture for low complexity massive MIMO systems. The GSM systems activates only small number of transmit antennas at a symbol time which simply the complexity in implementation. Different selection of the activating antennas patterns change the average symbol error rate (SER) performance, however the optimal selection of the activating antenna patterns is an NP hard problem due to the complicated connection in the universe of antenna patterns set. Through [1] has proposed a suboptimal design criterion for the codeword construction problem, it does not proposed the corresponding algorithms to realize the criterion. Even the suboptimal algorithm for the GSM codeword construction problem has not been proposed yet. Motivating by the above reasons, in this thesis we propose two GSM codeword construction criterions in the sense of minimizing the average symbol error rate (SER). We also design the corresponding systematic greedy-like algorithms for the proposed criterions and for the criterion proposed by [1]. At the last of the thesis we show the numerical results for the proposed codeword construction algorithms and we verify the performance of the proposed algorithms are indeed better than the algorithm whose design criterion is proposed by [1] and also better than the random selection method.

碩士<br>國立清華大學<br>電機工程學系<br>104<br>Massive multiple-input multiple-output system, has many advantages for wireless communication system, has higher data rate and accommodate more users. Due to generalized spatial modulation can effectively reduce hardware complexity and improve the spectral efficiency of multiple-input multiple-output system, it is a modulation method whitch combines the combination of transmit antennas and digital modulation as a transmission codeword and has been widely discussed in recent years. Nowadays, there are a lot of discussions about the hard-decision detections of generalized spatial modulation. The complexity of inverse matrix operations is high computational. Under these circumstances, we propose a detection method that is similar to tree search whitch has lower computation and present the soft-decision detections whitch is applicable to Low-density parity-check(LDPC) code. In view of the results, we have a tight performance loss compared to maximum a posteriori(MAP) detection.

碩士<br>國立中山大學<br>通訊工程研究所<br>107<br>Generalized spatial modulation (GSM) is a novel multiple-input-multiple-out (MIMO) technique, in which only several transmit antennas are activated in each time slot. Although the maximum likelihood (ML) detector is able to achieve the optimal performance, exhaustive search leads to computational complexity that is difficult to handle. In this paper, a search method called A-star algorithm is adopted, which uses a special heuristic function to directly remove some obviously poor paths. It can have lower complexity without losing performance. However, to determine the value of each node, we use the cost function of codebook-assisted hard decision (CAHD), which is a tree search system. CAHD is a low-complexity detector by setting the number of paths to be reserved for each layer. But when a certain signal is calculated, the other signals and noise are regarded as interference. This has a low complexity, but there is an error floor at high SNR. Our proposed algorithm effectively solves error floor of CAHD because we use the A-star search algorithm. This simulation results show that we can maintain the performance of ML, and the complexity is still lower than ML. On the other hand, we use different weights at different SNR to propose performance near-ML, but the complexity can be more significantly reduced.

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.

A rápida evolução dos sistemas de telecomunicações culminou numa necessidade cada vez mais crescente por redes que permitam elevados débitos. Associado a esse throughput elevado está o custo energético que gradualmente torna os sistemas pouco eficientes energeticamente. As modulações espaciais generalizadas (Generalized Spatial Modulation -GSM) surgem da necessidade de criar comunicações mais “verdes”, permitindo obter melhores eficiências energéticas através da redução do número de cadeias de blocos radio-frequência (RF) utilizadas no emissor. O estudo apresentado neste trabalho pretende realçar, num primeiro ponto, a importância da evolução dos sistemas de transmissão MIMO (Multiple-Input Multiple-Output) como forma de aumento do throughput global de uma rede de telecomunicações mantendo uma eficiência energética alta, com foco em GSM. O segundo ponto consiste no estudo de um algoritmo baseado no método ADMM (Alternating Direction Method of Multipliers), como recetor de baixa complexidade para esquemas GSM com desempenho próximo do ótimo, o detetor de máxima verosimilhança (MLD). O estudo do recetor ADMM foi efetuado em duas fases, sendo que a primeira é referente ao estudo extensivo e exclusivo do recetor ADMM, com principal enfoque nos vários parâmetros que o definem. Na segunda fase é feita uma comparação para vários cenários entre o recetor ADMM e alguns dos recetores de baixa complexidade mais conhecidos, entre eles o OB-MMSE (Ordered Block MMSE) e o BPDN (Basis Pursuit De-Noising), por exemplo. A realização de simulações, com os vários recetores, em vários cenários permitiu concluir que o ADMM, com recurso às suas técnicas de refinamento, representa uma alternativa eficiente, e em certos casos superior, ao OB-MMSE principalmente para cenários com um elevado número de bits por símbolo espacial.<br>The fast evolution of telecommunications systems resulted in a growing need for networks that support high transmission rates. Associated with this high throughput is the energy cost that gradually makes this systems less energy-efficient . The Generalized Spatial Modulation (GSM) arises from the need to create more "green" communication, allowing best energy efficiencies. The study presented in this thesis aims to highlight firstly, the importance of the development of MIMO (Multiple-Input Multiple-Output) transmission systems capable of increasing the overall throughput of a telecommunications network while maintaining high energy efficiency, focusing on GSM. The second relevant aspect is the study of an algorithm based on the ADMM (Alternating Direction Method of Multipliers) method, as a solution for a low complexity receiver for GSM schemes with a performance close to the optimal one, the maximum likelihood detector (MLD). The ADMM receiver study was conducted in two phases, the first of which refers to the extensive and unique study of the ADMM receiver, with main focus on the various parameters that define it. In the second stage a comparison is made between the settings for various ADMM receivers and some of the known low-complexity receivers, including OB-MMSE (Ordered Block MMSE) and BPDN (Basis Pursuit De-noising), for example. The results obtained from the evaluations performed several scenarios allow us to conclude that the ADMM based receiver combined with refinement techniques, is an efficient alternative and in some cases with better performance than the OB-MMSE receiver, especially for scenarios with a large number of bits per spatial symbol.

碩士<br>國立臺灣科技大學<br>電機工程系<br>107<br>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.

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.<br>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.