Detection and Resource Allocation Algorithms for Cooperative MIMO Relay Systems

Cooperative communications and multiple-input multiple-output (MIMO) communication systems are important topics in current research that will play key roles in the future of wireless networks and standards. In this thesis, the various challenges in accurately detecting and estimating data signals and allocating resources in the cooperative systems are investigated. Firstly, we propose a cross-layer design strategy that consists of a cooperative maximum likelihood (ML) detector operating in conjunction with link selection for a cooperative MIMO network. Two new link selection schemes are proposed, along with an iterative detection and decoding (IDD) scheme that utilises channel coding techniques. Simulation results show the performance and potential gains of the proposed schemes. Secondly, a successive interference cancellation (SIC) detector is proposed for a MIMO system that has dynamic ordering based on a reliability ordering (RO), and an alternative multiple feedback (MF) candidate cancellation method. The complexity of these schemes is analysed and a hard decision feedback IDD system is also proposed. Results show that the proposed detector can give gains over existing schemes for a minimal amount of extra complexity. Lastly, a detector is proposed that is based upon the method of widely linear (WL) filtering and a multiple branch (MB) SIC, for an overloaded, multi-user cooperative MIMO system. The use of WL methods is explained, and a new method of choosing cancellation branches for an MB detector is proposed with an analysis of the complexity required. A list-based IDD system is developed, and simulation results show that the proposed detector can operate in an overloaded system and provide improved performance gains

Unified bit-based probabilistic data association aided MIMO detection for high-order QAM constellations

A unified Bit-based Probabilistic Data Association (B-PDA) detection approach is proposed for Multiple-Input Multiple-Output (MIMO) systems employing high-order rectangular Quadrature Amplitude Modulation (QAM). The new approach transforms the symbol detection process of QAM to a bit-based process by introducing a Unified Matrix Representation (UMR) of QAM. Both linear natural and nonlinear binary reflected Gray bit-to-symbol mappings are considered. With the aid of simulation results, we demonstrate that the linear natural mapping based B-PDA approach typically attained an improved detection performance (measured in terms of both Bit Error Ratio (BER) and Symbol Error Ratio (SER)) in comparison to the conventional symbol-based PDA aided MIMO detector, despite its dramatically reduced computational complexity. The only exception is that at low SNRs, the linear natural mapping based B-PDA is slightly inferior in terms of its BER to the conventional symbol-based PDA using binary reflected Gray mapping. Furthermore, the simulation results show that the linear natural mapping based B-PDA MIMO detector may approach the best-case performance provided by the nonlinear binary reflected Gray mapping based B-PDA MIMO detector under ideal conditions. Additionally, the implementation of the B-PDA MIMO detector is shown to be much simpler in the case of the linear natural mapping. Based on these two points, we conclude that in the context of the uncoded B-PDA MIMO detector it is preferable to use the linear natural bit-to-symbol mapping, rather than the nonlinear Gray mapping

Récepteur itératif pour les systèmes MIMO-OFDM basé sur le décodage sphérique : convergence, performance et complexité

Recently, iterative processing has been widely considered to achieve near-capacity performance and reliable high data rate transmission, for future wireless communication systems. However, such an iterative processing poses significant challenges for efficient receiver design. In this thesis, iterative receiver combining multiple-input multiple-output (MIMO) detection with channel decoding is investigated for high data rate transmission. The convergence, the performance and the computational complexity of the iterative receiver for MIMO-OFDM system are considered. First, we review the most relevant hard-output and soft-output MIMO detection algorithms based on sphere decoding, K-Best decoding, and interference cancellation. Consequently, a low-complexity K-best (LCK- Best) based decoder is proposed in order to substantially reduce the computational complexity without significant performance degradation. We then analyze the convergence behaviors of combining these detection algorithms with various forward error correction codes, namely LTE turbo decoder and LDPC decoder with the help of Extrinsic Information Transfer (EXIT) charts. Based on this analysis, a new scheduling order of the required inner and outer iterations is suggested. The performance of the proposed receiver is evaluated in various LTE channel environments, and compared with other MIMO detection schemes. Secondly, the computational complexity of the iterative receiver with different channel coding techniques is evaluated and compared for different modulation orders and coding rates. Simulation results show that our proposed approaches achieve near optimal performance but more importantly it can substantially reduce the computational complexity of the system. From a practical point of view, fixed-point representation is usually used in order to reduce the hardware costs in terms of area, power consumption and execution time. Therefore, we present efficient fixed point arithmetic of the proposed iterative receiver based on LC-KBest decoder. Additionally, the impact of the channel estimation on the system performance is studied. The proposed iterative receiver is tested in a real-time environment using the MIMO WARP platform.Pour permettre l’accroissement de débit et de robustesse dans les futurs systèmes de communication sans fil, les processus itératifs sont de plus considérés dans les récepteurs. Cependant, l’adoption d’un traitement itératif pose des défis importants dans la conception du récepteur. Dans cette thèse, un récepteur itératif combinant les techniques de détection multi-antennes avec le décodage de canal est étudié. Trois aspects sont considérés dans un contexte MIMOOFDM: la convergence, la performance et la complexité du récepteur. Dans un premier temps, nous étudions les différents algorithmes de détection MIMO à décision dure et souple basés sur l’égalisation, le décodage sphérique, le décodage K-Best et l’annulation d’interférence. Un décodeur K-best de faible complexité (LC-K-Best) est proposé pour réduire la complexité sans dégradation significative des performances. Nous analysons ensuite la convergence de la combinaison de ces algorithmes de détection avec différentes techniques de codage de canal, notamment le décodeur turbo et le décodeur LDPC en utilisant le diagramme EXIT. En se basant sur cette analyse, un nouvel ordonnancement des itérations internes et externes nécessaires est proposé. Les performances du récepteur ainsi proposé sont évaluées dans différents modèles de canal LTE, et comparées avec différentes techniques de détection MIMO. Ensuite, la complexité des récepteurs itératifs avec différentes techniques de codage de canal est étudiée et comparée pour différents modulations et rendement de code. Les résultats de simulation montrent que les approches proposées offrent un bon compromis entre performance et complexité. D’un point de vue implémentation, la représentation en virgule fixe est généralement utilisée afin de réduire les coûts en termes de surface, de consommation d’énergie et de temps d’exécution. Nous présentons ainsi une représentation en virgule fixe du récepteur itératif proposé basé sur le décodeur LC K-Best. En outre, nous étudions l’impact de l’estimation de canal sur la performance du système. Finalement, le récepteur MIMOOFDM itératif est testé sur la plateforme matérielle WARP, validant le schéma proposé

Design and Implementation of Efficient Algorithms for Wireless MIMO Communication Systems

En la última década, uno de los avances tecnológicos más importantes que han hecho culminar la nueva generación de banda ancha inalámbrica es la comunicación mediante sistemas de múltiples entradas y múltiples salidas (MIMO). Las tecnologías MIMO han sido adoptadas por muchos estándares inalámbricos tales como LTE, WiMAS y WLAN. Esto se debe principalmente a su capacidad de aumentar la máxima velocidad de transmisión , junto con la fiabilidad alcanzada y la cobertura de las comunicaciones inalámbricas actuales sin la necesidad de ancho de banda extra ni de potencia de transmisión adicional. Sin embargo, las ventajas proporcionadas por los sistemas MIMO se producen a expensas de un aumento sustancial del coste de implementación de múltiples antenas y de la complejidad del receptor, la cual tiene un gran impacto sobre el consumo de energía. Por esta razón, el diseño de receptores de baja complejidad es un tema importante que se abordará a lo largo de esta tesis. En primer lugar, se investiga el uso de técnicas de preprocesado de la matriz de canal MIMO bien para disminuir el coste computacional de decodificadores óptimos o bien para mejorar las prestaciones de detectores subóptimos lineales, SIC o de búsqueda en árbol. Se presenta una descripción detallada de dos técnicas de preprocesado ampliamente utilizadas: el método de Lenstra, Lenstra, Lovasz (LLL) para lattice reduction (LR) y el algorimo VBLAST ZF-DFE. Tanto la complejidad como las prestaciones de ambos métodos se han evaluado y comparado entre sí. Además, se propone una implementación de bajo coste del algoritmo VBLAST ZF-DFE, la cual se incluye en la evaluación. En segundo lugar, se ha desarrollado un detector MIMO basado en búsqueda en árbol de baja complejidad, denominado detector K-Best de amplitud variable (VB K-Best). La idea principal de este método es aprovechar el impacto del número de condición de la matriz de canal sobre la detección de datos con el fin de disminuir la complejidad de los sistemasRoger Varea, S. (2012). Design and Implementation of Efficient Algorithms for Wireless MIMO Communication Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16562Palanci

Antenna selection and performance analysis of MIMO spatial multiplexing systems

Multiple-input multiple-output spatial multiplexing (MIMO-SM) systems offer an essential benefit referred to as spatial multiplexing gain. Two important signal reception techniques for MIMO-SM systems are the zero-forcing (ZF) and ordered successive interference cancellation (OSIC) as, for example, in the case of the decision-feedback detector (DFD). This thesis studies the communication and signal processing aspects of MIMO-SM. We first investigate the bit error rate (BER) performance of the ZF receiver over transmit correlated Ricean flat-fading channels. In particular, for a MIMO channel with M transmit and N receive antennas, we derive an approximation for the average BER of each sub-stream. A closed-form expression for the optimal transmit correlation coefficient, which achieves the maximum capacity (i.e., uncorrelated case) of two-input two-output spatial multiplexing (TITO-SM) systems, is presented. We further propose an antenna selection (AS) approach for the DFD over independent Rayleigh flat-fading channels. The selected transmit antennas are those that maximize both the post-processing signal-to-noise ratio (SNR) at the receiver end, and the system capacity. An upper bound on the outage probability for the AS approach is derived. It is shown that the AS approach achieves a performance comparable to optimal capacity-based selection based on exhaustive search, but at a lower complexity. Finally, we investigate a cross-layer transmit AS approach for the DFD over spatially correlated Ricean flat-fading channels. The selected transmit antennas are those that maximize the link layer throughput of correlated MIMO channels. A closed-form expression for the system throughput with perfect channel estimation is first derived. We further analyze the system performance with pilot-aided channel estimation. In that, we derive a closed-form expression for the post-detection signal-to-noise-plus-interference ratio (SNIR) of each transmitted substream, conditioned on the estimated channels. The derived SNIR is then used to evaluate the overall system throughput. It is observed that the cross-layer AS approach always assigns the transmission to the antenna combination which sees better channel conditions, resulting in a substantial improvement over the optimal capacity-based AS approach. Considering a training-based channel estimation technique, we compare the performance of the proposed cross-layer AS with that of optimal capacity-based AS when employed with a training-based channel estimation. Our results show that the latter is more robust to imperfect channel estimation. However, in all cases, the cross-layer AS delivers higher throughput gains than the capacity-based A

Space-time coding for mimo rayleigh fading systems

Ph.DDOCTOR OF PHILOSOPH

A Family of Hybrid Space-Time Codes for MIMO Wireless Communications

Hybrid MIMO space-time codes combine the benefits of spatial multiplexing with diversity gain to achieve both high spectral efficiency and link reliability. In this paper, we present a family of hybrid codes, known as LD STBC-VBLAST codes, along with a receiver architecture suitable for low-complexity hardware implementation. We show that, under Rayleigh fading, the performance of LD STBC-VBLAST codes is superior to other recently proposed hybrid codes. We also present a technique to derive, from a given propagation scenario, spatially correlated MIMO channel models adequate for space-time coding performance analysis. Using this technique, we evaluate the performance of LD STBC-VBLAST codes under several correlated channels.ITESO, A.C.ITSONCINVESTAV-IPNPROME

Improved QR Decomposition-Based SIC Detection Algorithm for MIMO System

Abstract: Multiple-Input Multiple-Output (MIMO) systems can increase wireless communication system capacity enormously. Maximum Likelihood (ML) detection algorithm is the optimum detection algorithm which computational complexity growing exponentially with the number of transmit-antennas, which makes it difficult to use it in practice system. Ordered Successive Interference Cancellation (SIC) algorithm with lower computing complexity will suffer from error propagation when an incorrect symbol is selected in the early layers. An MIMO signal detection algorithm based on Improved Sorted-QR decomposition (ISQR) is presented in this study. According to the rule of SNR, ISQR can obtain the optimum detection order with less calculation. Based on ISQR an improved detection algorithm is proposed which providing 2 adjustable parameters. Trade-off between performance and complexity can be selected properly by setting the 2 parameters at different values. Simulation experiments are given under the multiple scattering wireless communication environments and the simulation experiment results show the validity of proposed algorithm