Multi-user wireless systems with multiple antennas can drastically increase the capac- ity while maintaining the quality of service requirements. The best performance of these systems is obtained at the presence of instantaneous channel knowledge. Since uplink-downlink channel reciprocity does not hold in frequency division duplex and broadband time division duplex systems, efficient channel quantization becomes important. This thesis focuses on different quantization techniques in a linearly precoded multi-user wireless system. Our work provides three major contributions. First, we come up with an end-to-end transceiver design, incorporating precoder, receive combining and feedback policy, that works well at low feedback overhead. Second, we provide optimal bit allocation across the gain and shape of a complex vector to reduce the quantization error and investigate its effect in the multiuser wireless system. Third, we design an adaptive differential quantizer that reduces feedback overhead by utilizing temporal correlation of the channels in a time varying scenario.

Multi-user wireless systems with multiple antennas can drastically increase the capac- ity while maintaining the quality of service requirements. The best performance of these systems is obtained at the presence of instantaneous channel knowledge. Since uplink-downlink channel reciprocity does not hold in frequency division duplex and broadband time division duplex systems, efficient channel quantization becomes important. This thesis focuses on different quantization techniques in a linearly precoded multi-user wireless system. Our work provides three major contributions. First, we come up with an end-to-end transceiver design, incorporating precoder, receive combining and feedback policy, that works well at low feedback overhead. Second, we provide optimal bit allocation across the gain and shape of a complex vector to reduce the quantization error and investigate its effect in the multiuser wireless system. Third, we design an adaptive differential quantizer that reduces feedback overhead by utilizing temporal correlation of the channels in a time varying scenario.

This thesis investigates the application of an iterative leakage-based precoding algorithm to practical multiuser-MIMO systems. We consider the effect of practical impairments including imperfect channel state information, transmit antenna correlation, and time-varying channels. Solutions are derived which improve performance of the algorithm with imperfect channel state information at the transmitter by leveraging knowledge of the second-order statistics of the error. From this work we draw a number of conclusions on how imperfect channel state information may impact the system design including the importance of interference suppression at the receiver and the selection of the number of co-scheduled users. We also demonstrate an efficient approach to improve the convergence of the algorithm when using interference-rejection-combining receivers. Finally, we conduct simulations of an LTE-A system employing the improved algorithm to show its utility for modern communication systems. / Master of Science

Future wireless communications expect to experience a spectrum shortage problem. One practical solution is spectrum sharing. This thesis studies precoding strategies to allocate communication resources for spectrum sharing in multi-user wireless systems from a game-theoretic perspective. The approaches for the precoding games are developed under different constraints. It is shown that the precoding game with spectral mask constraints can be formulated as a convex optimization problem and a dual decomposition based algorithm can be exploited to solve it. However, the problem is non-convex if users also have total power constraints. This study shows that an efficient sub-optimal solution can be derived by allocating the bottleneck resource in the system. The sub-optimal solution is proved to be efficient and can even achieve an identical performance to that of the optimal solution in certain cases, but with significantly reduced complexity. / Communications

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.

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Massive MIMO systems are shown to be a promising technology for next generations of wireless communication networks. The realization of the attractive merits promised by massive MIMO systems requires advanced linear precoding and receiving techniques in order to mitigate the interference in downlink and uplink transmissions. This work considers the precoder and receiver design in massive MIMO systems. We first consider the design of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio (SINR) subject to a given power constraint. The analysis is carried out under the asymptotic regime in which the number of the BS antennas and that of the users grow large with a bounded ratio. This allows us to leverage tools from random matrix theory in order to approximate the parameters of the optimal linear precoder and receiver by their deterministic approximations. Such a result is of valuable practical interest, as it provides a handier way to implement the optimal precoder and receiver. To reduce further the complexity, we propose to apply the truncated polynomial expansion (TPE) concept on a per-user basis to approximate the inverse of large matrices that appear on the expressions of 4 the optimal linear transceivers. Using tools from random matrix theory, we determine deterministic approximations of the SINR and the transmit power in the asymptotic regime. Then, the optimal per-user weight coefficients that solve the max-min SINR problem are derived. The simulation results show that the proposed precoder and receiver provide very close to optimal performance while reducing significantly the computational complexity. As a second part of this work, the TPE technique in a per-user basis is applied to the optimal linear precoding that minimizes the transmit power while satisfying a set of target SINR constraints. Due to the emerging research field of green cellular networks, such a problem is receiving increasing interest nowadays. Closed form expressions of the optimal parameters of the proposed low complexity precoding for power minimization are derived. Numerical results show that the proposed power minimization precoding approximates well the performance of the optimal linear precoding while being more practical for implementation.

Future cellular networks are expected to support extremely high data rates and user capacities. This thesis investigates the downlink of a wireless cellular system that takes advantage of multiple antennas at base stations and mobile stations, frequency reuse across all cells, and cooperation among base stations. We identify asynchronous interference resulting from multi-cell communication as a key challenge, prove the existence of a downlink/uplink duality in that case, and present a linear precoding scheme that exploits this duality. Since this result is not directly extendable to orthogonal frequency division multiplexing (OFDM), we propose a `hybrid' algorithm for two cooperating base stations, which combines linear and nonlinear precoding. This algorithm minimizes the sum mean squared error of the system and is extendable to OFDM. Finally, we consider the problem of user selection for multiuser precoding in OFDM-based systems. We extend an available single-cell user selection scheme to multiple cooperating cells.

Future cellular networks are expected to support extremely high data rates and user capacities. This thesis investigates the downlink of a wireless cellular system that takes advantage of multiple antennas at base stations and mobile stations, frequency reuse across all cells, and cooperation among base stations. We identify asynchronous interference resulting from multi-cell communication as a key challenge, prove the existence of a downlink/uplink duality in that case, and present a linear precoding scheme that exploits this duality. Since this result is not directly extendable to orthogonal frequency division multiplexing (OFDM), we propose a `hybrid' algorithm for two cooperating base stations, which combines linear and nonlinear precoding. This algorithm minimizes the sum mean squared error of the system and is extendable to OFDM. Finally, we consider the problem of user selection for multiuser precoding in OFDM-based systems. We extend an available single-cell user selection scheme to multiple cooperating cells.

L’estimation de canal joue un rôle important dans les communications mobiles sans fil et en particulier dans les systèmes multi-antennes MIMO. Contrairement aux techniques classiques d’estimation de canal basées sur des séquences d’apprentissage ou des symboles pilotes, les techniques aveugles ne nécessitent aucune insertion de symboles d'apprentissage et permettent d'augmenter le débit utile. Les principales difficultés des techniques aveugles résident dans l’ambiguïté présente sur les estimées. Les techniques d’estimation semi-aveugles, basées sur les mêmes méthodes que l’estimation aveugle, sont plus robustes. Elles exploitent l’information aveugle ainsi que l’information provenant d’un nombre réduit de symboles d’apprentissage. Cette estimation du canal de communication est très utile dans les systèmes MIMO et permet de précoder le signal MIMO-OFDM en lui appliquant un pré-mélange permettant d'améliorer les performances. De nombreux types de précodeurs existent et leurs performances varient en fonction des critères d'optimisation retenus (Water-Filling, MMSE, Equal Error, max-SNR, max-d min …), mais aussi avec la qualité de l'estimation du canal de communication. Nous étudions dans cette thèse l’impact de l’utilisation de l’information du canal (CSI) provenant des méthodes d’estimation aveugle et semi-aveugle, dans l’application des précodeurs linéaires MIMO. Nous présentons également une étude statistique de l’erreur d’estimation provenant de ces méthodes. L’optimisation de ces précodeurs nous mène par la suite à exploiter un autre procédé permettant l’amélioration des performances : les codes correcteurs d’erreur. Nous nous intéressons particulièrement aux codes LDPC non-binaires et leur association avec les précodeurs linéaires MIMO. Nous montrons qu’une adaptation est possible et s’avère bénéfique dans certains cas. L’optimisation de cette association nous a permis de proposer un nouveau précodeur basé sur la maximisation de l’information mutuelle, robuste et plus performant. / Channel estimation plays an important role in wireless mobile communications, especially in MIMO systems. Unlike conventional channel estimation techniques based on training sequences or pilot symbols, blind techniques does not require the insertion of training symbols and allow higher throughput. The main problems of the blind lies in the ambiguity over the estimated channel. Based on the same methods as the blind estimation, the semi-blind estimation techniques are more robust. They exploit the blind information along with information provided by a small number of training symbols. The channel estimation is useful in MIMO systems and allows the precoding of the MIMO-OFDM signal by applying a pre-mixture in order to improve performance. Many types of precoders exist and their performance varies depending not only on the optimization criteria (Water-Filling, MMSE, Equal Error, max-SNR, max-d min ...), but also on the estimated channel. In this thesis we study the impact of using the channel information (CSI) from the blind and semi-blind estimation techniques to apply MIMO linear precoders. We also present a statistical study of the estimation error of these methods. The optimization of these precoders leads eventually to use another process allowing more performance improvement: the error correcting codes. We are particularly interested in non-binary LDPC codes and their association with linear MIMO precoders. We show that a matching is possible, and is beneficial in some cases. The optimization of this combination has allowed us to propose a new robust and more efficient precoder based on the maximization of mutual information.