Nowadays, multiuser Multiple-In Multiple-Out systems (MU-MIMO) are used in a new generation wireless technologies. Due to that wireless technology improvement is ongoing, the numbers of users and applications increase rapidly. Then, wireless communications need the high data rate and link reliability at the same time. Therefore, MU-MIMO improvements have to consider 1) providing the high data rate and link reliability, 2) support all users in the same time and frequency resource, and 3) using low power consumption. In practice, the interuser interference has a strong impact when more users access to the wireless link. Complicated transmission techniques such as interference cancellation should be used to maintain a given desired quality of service. Due to these problems, MU-MIMO with very large antenna arrays (known as massive MIMO) are proposed. With a massive MU-MIMO system, we mean a hundred of antennas or more serving tens of users. The channel vectors are nearly orthogonal, and then the interuser interference is reduced significantly. Therefore, the users can be served with high data rate simultaneously. In this thesis, we focus on the performance of the massive MU-MIMO downlink where the base station uses linear precoding techniques to serve many users over Rayleigh and Nakagami-m fading channels.

Next generation wireless systems will use multiple antenna technologies, also known as multiple-input multiple-output (MIMO), to provide high data rates and robustness against fading. MIMO communication strategies for single user communication systems and their practical application in wireless networks are by now well known. MIMO communication systems, however, can benefit from multiuser processing by coordinating the transmissions to multiple users simultaneously. For numerous reasons, work on the theory of multiuser MIMO communication has yet to see broad adoption in wireless communication standards. For example, global knowledge of channel state information is often required. Such an unrealistic assumption, however, makes it difficult in practice to implement precoding techniques. Furthermore, the achievable rates of the conventional multiuser MIMO techniques are far from the theoretical performance bounds. These and other factors motivate research on practical multiuser communication strategies for the MIMO broadcast channel (point to multi-point communication) and the analysis of those strategies. The primary contributions of this dissertation are i) the development of four novel low complexity coordinated MIMO transceiver design techniques to approach the theoretical performance bound and ii) the investigation of the optimality of the proposed coordinated wireless MIMO networks. Several coordinated beamforming algorithms are proposed, where each mobile station uses quantized combining vectors or each base station uses limited feedback from the MS. The asymptotic optimality of the proposed coordinated beamforming system for the MIMO Gaussian broadcast channel is next investigated. For multi-stream transmission, a novel block diagonalized vector perturbation is proposed and the achievable sum rate upper bound of the proposed system is derived. Finally, for multi-cell environments, linear and non-linear network CBF algorithms supporting multiple cell-boundary users are proposed. The optimality of network coordinated beamforming in terms of the number of receive antennas is also investigated. / text

The use of multiple antennas to improve the reliability and capacity of wireless communication has been around for a while, leading to the concept of multiple-input multiple-output (MIMO) communications. To enable full MIMO potentials, the precoding design has been recognized as a crucial component. This thesis aims to design multiuser MIMO precoders of practical interest to achieve high reliability and capacity performance under various real-world constraints like inaccuracy of channel information acquired at the transmitter, hardware complexity, etc. Three prominent cases are considered which constitute the mainstream evolving directions of the current cellular communication standards and future 5G cellular communications. First, in a relay-assisted multiuser MIMO system, heavily quantized channel information obtained through limited feedback contributes to noticeable rate loss compared to when perfect channel information is available. This thesis derives an upper bound to characterize the system throughput loss caused by channel quantization error, and then develops a feedback quality control strategy to maintain the rate loss within a bounded range. Second, in a massive multiuser MIMO channel, due to the large array size, it is difficult to support each antenna with a dedicated radio frequency chain, thus making high-dimensional baseband precoding infeasible. To address this challenge, a low-complexity hybrid precoding scheme is designed to divide the precoding into two cascaded stages, namely, the low-dimensional baseband precoding and the high-dimensional phase-only processing at the radio frequency domain. Its performance is characterized in a closed form and demonstrated through computer simulations. Third, in a mmWave multiuser MIMO scenario, smaller wavelengths make it possible to incorporate excessive amounts of antenna elements into a compact form. However, we are faced with even worse hardware challenges as mixed signal processing at mmWave frequencies is more complex and power consuming. The channel sparsity is taken advantage of in this thesis to enable a simplified precoding scheme to steer the beam for each user towards its dominant propagation paths at the radio frequency domain only. The proposed scheme comes at significantly reduced complexity and is shown to be capable of achieving highly desirable performance based on asymptotic rate analysis. / Graduate

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.

abstract: Underwater acoustic communications face significant challenges unprecedented in radio terrestrial communications including long multipath delay spreads, strong Doppler effects, and stringent bandwidth requirements. Recently, multi-carrier communications based on orthogonal frequency division multiplexing (OFDM) have seen significant growth in underwater acoustic (UWA) communications, thanks to their well well-known robustness against severely time-dispersive channels. However, the performance of OFDM systems over UWA channels significantly deteriorates due to severe intercarrier interference (ICI) resulting from rapid time variations of the channel. With the motivation of developing enabling techniques for OFDM over UWA channels, the major contributions of this thesis include (1) two effective frequencydomain equalizers that provide general means to counteract the ICI; (2) a family of multiple-resampling receiver designs dealing with distortions caused by user and/or path specific Doppler scaling effects; (3) proposal of using orthogonal frequency division multiple access (OFDMA) as an effective multiple access scheme for UWA communications; (4) the capacity evaluation for single-resampling versus multiple-resampling receiver designs. All of the proposed receiver designs have been verified both through simulations and emulations based on data collected in real-life UWA communications experiments. Particularly, the frequency domain equalizers are shown to be effective with significantly reduced pilot overhead and offer robustness against Doppler and timing estimation errors. The multiple-resampling designs, where each branch is tasked with the Doppler distortion of different paths and/or users, overcome the disadvantages of the commonly-used single-resampling receivers and yield significant performance gains. Multiple-resampling receivers are also demonstrated to be necessary for UWA OFDMA systems. The unique design effectively mitigates interuser interference (IUI), opening up the possibility to exploit advanced user subcarrier assignment schemes. Finally, the benefits of the multiple-resampling receivers are further demonstrated through channel capacity evaluation results. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011

Pour les prochaines générations de systèmes de communications sans fil, un défi majeur est de poursuivre l'augmentation de l' efficacité spectrale de ces systèmes pour satisfaire la montée croissante des demandes en débit, tout en revoyant à la baisse la consommation énergétique des équipements et répondre ainsi aux objectifs des ''communications vertes’’. L'une des stratégies permettant de traiter ce problème sont les communications multiantennes multi-utilisateurs (MU-MIMO), notamment lorsque le nombre d'antennes devient très grand (Massive MIMO). Il est alors possible d'adresser de multiples utilisateurs simultanément grâce à une opération linéaire de précodage spatial. Le but de cette thèse consiste à optimiser l’efficacité spectrale des systèmes MU-MIMO dans le cas d'un nombre d'antennes qui reste modéré, et une consommation énergétique faible. Nous avons donc étudié les techniques de précodage à haute efficacité énergétique basées sur la notion de filtre adapté au canal, tels que la technique MRT (maximum ratio transmission), EGT (equal gain transmission) et TR (time reversal). Notre travail s'est concentré sur l’analyse théorique des performances de ces techniques. Nous avons de plus introduit un nouveau schéma de transmission, nommé PFBO (partial frequency bandwidth overlay), visant à améliorer l’efficacité spectrale des systèmes MU-MIMO à faible nombre d'antennes et pour de faibles niveaux de rapports signal à bruit (SNR). Dans une première partie, nous avons étudié l'efficacité spectrale du schéma PFBO dans le cas de transmissions mono-porteuses et multi-porteuses. Les taux de recouvrement optimaux fournissant une capacité système maximale dans le cas de transmissions MISO et MIMO à deux utilisateurs ont été identifiés. Puis l'étude a été étendue aux cas MU-MIMO avec un nombre arbitraire d'utilisateurs. Nous avons modélisé précisément le comportement du canal équivalent après précodage, en utilisant respectivement les techniques EGT, TR et MRT. De nouvelles bornes de capacité non disponibles dans la littérature ont alors été obtenues et ont montré une précision satisfaisante. Dans la deuxième partie, le taux d'erreur binaire pour le schéma PFBO a été étudié sur canal plat et canal de Rayleigh. Les expressions du taux d'erreurs binaires ont été obtenues. En particulier, nous avons proposé un modèle statistique pour rendre compte du comportement du canal après précodage ainsi que de l'interférence inter-utilisateur. Une première proposition de modèle a été introduite pour les systèmes EGTMIMO à deux utilisateurs utilisant une modulation BPSK. Ce modèle a été également validé dans le cas d'une modulation QPSK ou pour de multiples utilisateurs. Dans la dernière partie, nous avons combiné le principe du schéma PFBO aux systèmes OFDM à spectre étalé (SSOFDM). Nous avons analysé les performances théoriques de ce système sur canal plat et canal de Rayleigh. Les expressions de taux d'erreurs binaires ont été établies et validées par simulations. Nous avons alors pu montrer que la composante SS permettait d'améliorer les performances du schéma PFBO lorsque le taux de recouvrement restait modéré. / For the next generations of wireless communication systems, getting higher spectral efficiencies is remaining a big challenge to answer the explosively increasing demand of throughput. Meanwhile, the energy consumption of equipments and the transmitting power density have to be reduced to achieve the objective of ‘’green communications’’. One of the most promising strategies to deal with such issues is using multi-user multiple-input multiple-output (MU-MIMO) schemes, namely for large-scale antenna systems. It becomes then possible to simultaneously serve multiple simple device users using linear spatial precoding techniques. The objective of this thesis is to optimize the spectral efficiency of MU-MIMO systems in the context of moderate-scale antenna arrays and low energy consumption. Hence, we studied different high-energy efficiency precoding techniques based on matched filtering approach, such as maximum ratio transmission (MRT), equal gain transmission (EGT) and time reversal (TR). We were interested in the theoretical performance analysis of these techniques. In addition, we introduced a scheme based on partial frequency bandwidth overlay (PFBO) to improve and adapt the spectral efficiency of a MU-MIMO system at low signal to noise ratio (SNR) regime. In a first part, we studied the spectral efficiency of the proposed PFBO scheme with both single-carrier and multi-carrier modulations. We identified the optimal bandwidth overlap ratios that provide the maximum achievable rate for two-user SIMO and MIMO systems. Then the study was extended to a more general MU-MIMO case with an arbitrary number of users. We precisely modeled the channel behavior after precoding when using EGT, TR and MRT techniques. New closed-form capacity lower bounds not available in the literature were then obtained and shown to be satisfactory accurate. In the second part, the bit error rate (BER) performance of PFBO scheme was studied for both flat fading channels and theoretical Rayleigh channels. Closed-form BER equations were obtained. Particularly, we proposed a statistical model to reflect the behavior of the non-flat fading channel after precoding and to take into account the correlated interference terms that occur in a two-user EGT-MIMO system using BPSK modulation. This model was also validated in case of QPSK modulation and with more users. In the last part, we proposed to combine our PFBO principle with spread-spectrum OFDM techniques (SS-OFDM). We analyzed the theoretical BER performance of such a scheme using flat fading channels and theoretical Rayleigh channels. New closed-form BER approximation equations were then established and compared through simulations. Eventually, we showed that the SS component of the proposed system provides performance gains that depend on the overlap ratio used in the PFBO scheme.

Abstract Radio resource management techniques for broadband wireless systems beyond the existing cellular systems are developed while considering their special characteristics such as multi-carrier techniques, adaptive radio links and multiple-input multiple-output (MIMO) antenna techniques. Special focus is put on the design of linear transmission strategies in a cooperative cellular system where signal processing can be performed in a centralised manner across distributed base station (BS) antenna heads. A time-division duplex cellular system based on orthogonal frequency division multiplexing (OFDM) with adaptive MIMO transmission is considered in the case where the received signals are corrupted by non-reciprocal inter-cell interference. A bandwidth efficient closed-loop compensation algorithm combined with interference suppression at the receiver is proposed to compensate for the interference and to guarantee the desired Quality of Service (QoS) when the interference structure is known solely at the receiver. A greedy beam ordering and selection algorithm is proposed to maximise the sum rate of a multiuser MIMO downlink (DL) with a block zero forcing (ZF) transmission. The performance of the block-ZF transmission combined with the greedy scheduling is shown to approach the sum capacity as the number of users increases. The maximum sum rate is often found to be achieved by transmitting to a smaller number of users or beams than the spatial dimensions allow. In addition, a low complexity algorithm for joint user, bit and power allocation with a low signalling overhead is proposed. Different linear transmission schemes, including the ZF as a special case, are developed for the scenario where the cooperative processing of the transmitted signal is applied to users located within a soft handover (SHO) region. The considered optimisation criteria include minimum power beamformer design; balancing the weighted signal-to-interference-plus-noise ratio (SINR) values per data stream; weighted sum rate maximisation; and balancing the weighted rate per user with additional QoS constraints such as guaranteed bit rate per user. The method can accommodate supplementary constraints, e.g., per antenna or per BS power constraints, and upper/lower bounds for the SINR values of the data streams. The proposed iterative algorithms are shown to provide powerful solutions for difficult non-convex transceiver optimisation problems. System level evaluation is performed in order to assess the impact of a realistic multi-cell environment on the performance of a cellular MIMO-OFDM system. The users located in the SHO region are shown to benefit from greatly increased transmission rates. Consequently, significant overall system level gains result from cooperative SHO processing. The proposed SHO scheme can be used for providing a more evenly distributed service over the entire cellular network.

The ever-growing demand of wireless traffic poses a challenge for current cellular networks. Each new generation must find new ways to boost the network capacity and spectral efficiency (SE) per device. A pillar of 5G is massive multiple-input-multiple-output (MIMO) technology. Through utilizing a large number of antennas at each transmitting node, massive MIMO has the ability to multiplex several user equipments (UEs) on the same time-frequency resources via spatial multiplexing. Looking beyond 5G, cell-free massive MIMO has attracted a lot of attention for its ability to utilize spatial macro diversity and higher resilience to interference. The cell-free architecture is based on a large number of distributed access points (APs) jointly serving the UEs within a coverage area without creating artificial cell boundaries. It provides a promising solution that is focused on delivering uniform service quality throughout the mobile network. The main challenges of the cell-free network architecture lie in the computational complexity for signal processing and the huge fronthaul requirements for information exchange among the APs. In this thesis, we tackle some of the inherent problems of the cell-free network architecture by providing distributed solutions to the power allocation and mobility management problems. We then introduce a new method for characterizing unknown interference in wireless networks. For the problem of power allocation, a distributed learning-based solution that provides a good trade-off between SE performance and applicability for implementation in large-scale networks is developed with reduced fronthaul requirements and computational complexity. The problem is divided in a way that enables each AP (or group of APs) to separately decide on the power coefficients to the UEs based on the locally available information at the AP without exchanging information with the other APs, however, still attempting to achieve a network wide optimization objective.  Regarding mobility management, a handover procedure is devised for updating the serving sets of APs and assigned pilot to each UE in a dynamic scenario considering UE mobility. The algorithm is tailored to reduce the required number of handovers per UE and changes in pilot assignment. Numerical results show that our proposed solution identifies the essential refinements since it can deliver comparable SE to the case when the AP-UE association is completely redone. Finally, we developed a new technique based on a Bayesian approach to model the distribution of the unknown interference arising from scheduling variations in neighbouring cells. The method is shown to provide accurate modelling for the unknown interference power and an effective tool for robust rate allocation in the uplink with a guaranteed target outage performance. / Den ständigt växande efterfrågan på trådlös datatrafik är en stor utmaning för dagens mobilnät. Varje ny nätgeneration måste hitta nya sätt att öka den totala kapaciteten och spektraleffektiviteten (SE) per uppkopplad enhet. En pelare i 5G är massiv-MIMO-teknik (multiple-input-multiple-output). Genom att använda ett stort antal antenner på varje mobilmast har massiv MIMO förmågan att kommunicera med flera användarutrustningar (eng. user equipment, UE) på samma tid/frekvensresurser via så kallad rumslig multiplexing. Om man ser bortom 5G-tekniken så har cellfri massiv-MIMO väckt stort intresse tack vare sin förmåga att utnyttja rumslig makrodiversitet för att förbättra täckningen och uppnå högre motståndskraft mot störningar. Den cellfria arkitekturen bygger på att ha ett stort antal distribuerade accesspunkter (AP) som gemensamt serverar UE:erna inom ett täckningsområde utan att dela upp området konstgjorda celler. Detta är en lovande lösning som är fokuserad på att leverera enhetliga datahastigheter i hela mobilnätet. De största forskningsutmaningarna med den cellfria nätverksarkitekturen ligger i beräkningskomplexiteten för signalbehandling och de enorma kraven på fronthaul-kablarna som möjliggör informationsutbyte mellan AP:erna. I den här avhandlingen löser vi några av de grundläggande utmaningarna med den cellfria nätverksarkitekturen genom att tillhandahålla distribuerade algoritmlösningar på problem relaterade till signaleffektreglering och mobilitetshantering. Vi introducerar sedan en ny metod för att karakterisera okända störningar i trådlösa nätverk. När det gäller signaleffektreglering så utvecklas en distribuerad inlärnings-baserad metod som ger en bra avvägning mellan SE-prestanda och tillämpbarhet för implementering i storskaliga cellfria nätverk med reducerade fronthaulkrav och lägre beräkningskomplexitet. Lösningen är uppdelat på ett sätt som gör det möjligt för varje AP (eller grupp av AP) att separat besluta om effektkoefficienterna relaterade till varje UE baserat på den lokalt tillgängliga informationen vid AP:n utan att utbyta information med de andra AP:erna, men ändå försöka uppnå ett nätverksomfattande optimeringsmål. När det gäller mobilitetshantering utformas en överlämningsprocedur som dynamiskt uppdaterar vilken uppsättning av AP:er som servar en viss UE och vilken pilotsekvens som används när den rör sig över täckningsområdet. Algoritmen är skräddarsydd för att minska antalet överlämningar per UE och förändringar i pilottilldelningen. Numeriska resultat visar att vår föreslagna lösning identifierar de väsentliga förfiningarna eftersom den kan leverera jämförbar SE som när AP-UE-associationen görs om helt och hållet. Slutligen utvecklade vi en ny Bayesiansk metod för att modellera den statistiska fördelningen av de okända störningarna som uppstår på grund av schemaläggningsvariationer i närliggande celler. Metoden har visat sig ge en korrekt modell av den okända störningseffekten och är ett effektivt verktyg för robust SE-allokering i upplänken med en garanterad maximal avbrottsnivå. / <p>QC 20230503</p>