The problem of detecting a vector of symbols, drawn from a finite alphabet and transmitted over a multiple-input multiple-output (MIMO) channel with Gaussian noise, is of central importance in digital communications and is encountered in several different applications. Examples include, but are not limited to; detection of symbols spatially multiplexed over a multiple-antenna channel and the multiuser detection problem in a code division multiple access (CDMA) system. Two algorithms previously proposed in the literature are considered and analyzed. Both algorithms have their origin in other fields of science but have gained mainstream recognition as efficient algorithms for the detection problem considered herein. Specifically, we consider the sphere decoder and semidefinite relaxation detector. By incorporating assumptions applicable in the communications context the performance of the two algorithms is addressed. The first algorithm, the sphere decoder, offers optimal performance in terms of its error probability. Further, the algorithm has proved extremely efficient in terms of computational complexity for moderately sized problems at high signal to noise ratio (SNR). Although it is recognized that the algorithm has an exponential worst case complexity, there has been a widespread belief that the algorithm has a polynomial average complexity at high SNR. A contribution made herein is to show that this is incorrect and that the average complexity, as the worst case complexity, is exponential in the number of symbols detected. Instead, another explanation of the observed efficiency of the algorithm is offered by deriving the exponential rate of growth and showing that this rate, although strictly positive for finite SNR, is small in the high SNR regime. The second algorithm, the semidefinite relaxation (SDR) detector, offers polynomial complexity at the expense of suboptimal performance in terms of error probability. Nevertheless, previous numerical observations suggest that error probability of the SDR algorithm is close to that of the optimal detector. Herein, the near optimality is of the SDR algorithm is given a precise meaning by studying the diversity of the SDR algorithm when applied to the (real valued) i.i.d.~Rayleigh fading channel and it is shown that the SDR algorithm achieves the same diversity order as the optimal detector. Further, criteria under which the SDR estimates coincide with the optimal estimates are derived and discussed. / Ett grundläggande problem som påträffats inom digital kommunikation är detektering av en symbolvektor, tillhörande ett ändligt symbolalfabet, som sänts över en MIMO (från engelskans multiple-input multiple-output) kanal med Gausiskt brus. Detta problem påträffas bland annat då symboler sänts över en trådlös kanal med flera antenner hos mottagaren och sändaren samt då flera användare i ett CDMA system simultant skall avkodas. In denna avhandling behandlas två mottagaralgoritmer konstruerade för detta ändamål. Algoritmerna har sin bakgrund i andra forskningsområden men kan i nuläget sägas vara mycket välkända inom kommunikationsområdet. De benämns vanligtvis som sfäravkodaren (eng. sphere decoder) samt den semidefinita relaxeringsdetektorn (eng. semidefinite relaxation detector). Algoritmerna analyseras i denna avhandling matematiskt genom att införa förenklande antaganden som är relevanta och applicerbara för de kommunikationsproblem som är av intesse. Den första algoritmen, sfäravkodaren, löser dessa detektionsproblem på ett optimalt sätt i betydelsen att den minimerar sannolikheten för att detektorn fattar ett felaktigt beslut rörande det sända meddelandet (symbolvektorn). Också vad gäller algoritmens komplexitet har simuleringar visat att den är oväntat låg, åtminstone vid höga signalbrusförhållanden (SNR). Trots att det är allmänt känt att algoritmen i sämsta fall har exponentiell komplexitet så har detta lett till den allmänt spridda uppfattningen att medelkomplexiteten (eller den förväntade komplexiteten) endast är polynomisk vid höga signalbrusförhållanden. Ett av huvudbidragen i denna avhandling är att visa att denna uppfattning är felaktig och att också medelkomplexiteten växer exponentiellt i antalet symboler som simultant detekteras. Ytterligare ett bidrag ligger i att ge en alternativ förklaring till den observerat låga medelkomplexiteten. Det visas att den exponentiella hastighet med vilken komplexiteten växer beror på signalbrusförhållande, och att den är låg för höga SNR. Den andra algoritmen, den semidefinita relaxeringsdetektorn, erbjuder polynomisk komplexitet vid en något högre felsannolikhet. Intressant nog har dock felsannolikheten tidigare, genom simuleringar, visat sig vara endast marginellt högre än felsannolikheten hos den optimala mottagaren. Bidraget som relaterar till den semidefinita relaxeringsmottagaren ligger i att både förklara och i att ge en specifik kvatifierbar mening åt uttalandet att felsannolikheten endast är marginellt högre. I syfte att åstadkomma detta studeras diversitetsordningen för detektorn, och det bevisas att diversitetsordningen för den semidefinita relaxeringsdetektorn är densamma som för den optimala mottagaren. Utöver detta karakteriseras också de krav som måste uppfyllas för att den detektorn skall finna den optimala lösningen. / QC 20100901

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

In this dissertation the aim was to investigate the usage of algorithms found in computer science and apply suitable algorithms to the problem of decoding multiple-input multipleoutput (MIMO) space-time-frequency block coded signals. It was found that the sphere decoder is a specific implementation of the A* tree search algorithm that is well known in computer science. Based on this knowledge, the sphere decoder was extended to include a priori information in the maximum a posteriori probability (MAP) joint decoding of the STFC block coded MIMO signals. The added complexity the addition of a priori information has on the sphere decoder was investigated and compared to the sphere decoder without a priori information. To mitigate the potential additional complexity several algorithms that determine the order in which the symbols are decoded were investigated. Three new algorithms incorporating a priori information were developed and compared with two existing algorithms. The existing algorithms compared against are sorting based on the norms of the channel matrix columns and the sorted QR decomposition. Additionally, the zero forcing (ZF) and minimum mean squared error (MMSE) decoderswith and without decision feedback (DF) were also extended to include a priori information. The developed method of incorporating a priori information was compared to an existing algorithm based on receive vector translation (RVT). The limitation of RVT to quadrature phase shift keying (QPSK) and binary shift keying (BPSK) constellations was also shown in its derivation. The impact of the various symbol sorting algorithms initially developed for the sphere decoder on these decoders was also investigated. The developed a priori decoders operate in the log domain and as such accept a priori information in log-likelihood ratios (LLRs). In order to output LLRs to the forward error correcting (FEC) code, use of the max-log approximation, occasionally referred to as hard-to-soft decoding, was made. In order to test the developed decoders, an iterative turbo decoder structure was used together with an LDPC decoder to decode threaded algebraic space-time (TAST) codes in a Rayleigh faded MIMO channel. Two variables that have the greatest impact on the performance of the turbo decoder were identified: the hard limit value of the LLRs to the LDPC decoder and the number of independently faded bits in the LDPC code. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Electrical, Electronic and Computer Engineering / unrestricted

Dans les télécommunications, le débit-fiabilité et la complexité de l’encodage et du décodage (opération à virgule flottante-flops) sont largement reconnus comme représentant des facteurs limitant interdépendants. Pour cette raison, tout tentative de réduire la complexité peut venir au prix d’une dégradation substantielle du taux d’erreurs. Cette thèse traite de l’établissement d’un compromis limite fondamental entre la fiabilité et la complexité dans des systèmes de communications « outage »-limités à entrées et sorties multiples (MIMO), et ses scénarios point-à-point, utilisateurs multiple, bidirectionnels, et aidés de feedback. Nous explorons un large sous-ensemble de la famille des méthodes d’encodage linéaire Lattice, et nous considérons deux familles principales de décodeurs : les décodeurs à maximum de vraisemblance (ML) et les décodeurs Lattice. L‘analyse algorithmique est concentrée sur l’implémentation de ces décodeurs ayant comme limitation une recherche bornée, ce qui inclue une large famille de sphère-décodeurs. En particulier, le travail présenté fournit une analyse à haut rapport Signal-à-Bruit (SNR) de la complexité minimum (flops ou taille de puce électronique) qui permet d’atteindre a) une certaine performance vis-à-vis du compromis diversité-gain de multiplexage et b) une différence tendant vers zéro avec le non-interrompu (optimale) ML décodeur, ou une différence tendant vers zéro comparé à l’implémentation exacte du décodeur (régularisé) Lattice. L’exposant de complexité obtenu décrit la vitesse asymptotique d’accroissement de la complexité, qui est exponentielle en terme du nombre de bits encodés. / In telecommunications, rate-reliability and encoding-decoding computational complexity (floating point operations - flops), are widely considered to be limiting and interrelated bottlenecks. For this reason, any attempt to significantly reduce complexity may be at the expense of a substantial degradation in error-performance. Establishing this intertwined relationship constitutes an important research topic of substantial practical interest. This dissertation deals with the question of establishing fundamental rate, reliability and complexity limits in general outage-limited multiple-input multiple-output (MIMO) communications, and its related point-to-point, multiuser, cooperative, two-directional, and feedback-aided scenarios. We explore a large subset of the family of linear lattice encoding methods, and we consider the two main families of decoders; maximum likelihood (ML) based and lattice-based decoding. Algorithmic analysis focuses on the efficient bounded-search implementations of these decoders, including a large family of sphere decoders. Specifically, the presented work provides high signal-to-noise (SNR) analysis of the minimum computational reserves (flops or chip size) that allow for a) a certain performance with respect to the diversity-multiplexing gain tradeoff (DMT) and for b) a vanishing gap to the uninterrupted (optimal) ML decoder or a vanishing gap to the exact implementation of (regularized) lattice decoding. The derived complexity exponent describes the asymptotic rate of exponential increase of complexity, exponential in the number of codeword bits.

No description available.

The reliability and data rate of wireless communication have traditionally been limited by the presence of multipath fading in wireless channels. However, dramatic performance improvements can be obtained by the use of multiple transmit and receive antennas. Specifically, multiple antennas increase reliability by providing diversity gain, namely greater immunity to deep channel fades. They also increase data rates by providing multiplexing gain, i.e., the ability to multiplex multiple symbols in one signaling interval. Harvesting the potential benefits of multiple antennas requires the use of specially designed space-time codes at the transmitter front-end. Space-time codes introduce redundancy in the transmitted signal across two dimensions, namely multiple transmit antennas and multiple signaling intervals. In this work, we focus on linear space-time codes, which linearly combine the real and imaginary parts of their complex inputs to obtain transmit vectors for multiple signaling intervals. We aim to design optimum linear space-time codes. Optimality metrics and design principles for space-time codes are shown to depend strongly on the codes' function in the overall transmitter architecture. We consider two cases, depending on whether or not the space-time code is complemented by a powerful outer error-control code. In the absence of an outer code, the multiplexing gain of a space-time code is measured by its rate, while its diversity gain is measured by its raw diversity order. To maximize multiplexing and diversity gains, the space-time code must have maximum possible rate and raw diversity order. We show that there is an infinite set of maximum-rate codes, almost all of which also have maximum raw diversity order. However, different codes in this set have different error rate for a given input alphabet and SNR. Therefore, we develop analytical and numerical optimization techniques to find the code in this set which has the minimum union bound on error rate. Simulation results indicate that optimized codes yield significantly lower error rates than unoptimized codes, at the same data rate and SNR. In a concatenated architecture, a powerful outer code introduces redundancy in the space-time code inputs, obtaining additional diversity. Thus, the raw diversity order of the space-time inner code is only a lower limit to the total diversity order of the concatenated transmitter. On the other hand, we show that the rate of the space-time code places an upper limit on the multiplexing ability of the concatenated architecture. We conclude that space-time inner codes should have maximum possible rate but need not have high raw diversity order. In particular, the serial-to-parallel converter, which introduces no redundancy at all, is a near-optimum space-time inner code. This claim is supported by simulation results. On the receiver side, we generalize the well known sphere decoder to develop new detection algorithms for stand-alone space-time codes. These new algorithms are extended to obtain efficient soft-output decoding algorithms for space-time inner codes.

Cette thèse traite des systèmes MIMO à multiplexage spatial, associés à la modulation OFDM. L'étude s'attarde particulièrement sur les systèmes 4x4, inclus ou à l'étude dans les normes 3GPP LTE et 3GPP LTE-A. Ces dimensions particulières nécessitent une étude de conception poussée du récepteur. Il s'agit notamment de proposer des détecteurs qui affichent à la fois de bonnes performances, une faible latence et une complexité de calcul réalisable dans un système embarqué. Le défi consiste plus particulièrement à proposer un détecteur offrant des performances quasi-optimales, tout en ne nécessitant qu'une complexité de calcul polynomiale. Une attention particulière est prêtée aux problèmes d'implantation. Ainsi, avantage est donné aux algorithmes à complexité fixe et permettant la réalisation d'opérations en parallèle. En réponse aux problématiques rencontrées, l'architecture du détecteur requiert une attention particulière. Le choix stratégique adopté est de chercher à transférer au prétraitement - qui ne dépend pas des données - le plus possible de complexité de calcul. Au cours de ce travail et suite à l'introduction du contexte général et des principaux pré-requis, l'inventaire des grandes tendances dans la littérature en ce qui concerne les détecteurs à décision dure est fait. Ils constituent le coeur du sujet et un détecteur original est proposé, incluant notamment les aspects de réduction de réseau et de décodage sphérique. Son avantage par rapport aux techniques existantes est ainsi démontré, et les résultats prometteurs sont maintenus lors de son extension à la décision souple. Comme attendu, le choix de transférer au prétraitement la complexité de calcul s'avère gagnant. Notamment, la réduction de complexité de calcul qu'il permet est présentée dans cette thèse. Parmi les principaux résultats, ce travail a débouché sur la proposition d'un détecteur original, qui a démontré un compromis entre performance et complexité de calcul efficace. Notamment, il requiert une complexité de calcul presque constante - selon les tailles de constellation -, tout en offrant des performances proches du maximum de vraisemblance. Par conséquent, le détecteur à décision souple proposé se positionne par rapport à l'état de l'art comme une solution d'une grande efficacité dans les systèmes 4x4.

The aim of the dissertation was to design a realistic, low-complexity non-binary (NB) low density parity check (LDPC) coded space-time-frequency (STF) coded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with an iterative joint decoder and detector structure at the receiver. The goal of the first part of the dissertation was to compare the performance of different design procedures for NB-LDPC codes on an additive white Gaussian noise (AWGN) channel, taking into account the constraint on the code length. The effect of quantisation on the performance of the code was also analysed. Different methods for choosing the NB elements in the parity check matrix were compared. For the STF coding, a class of universal STF codes was used. These codes use linear pre-coding and a layering approach based on Diophantine numbers to achieve full diversity and a transmission rate (in symbols per channel use per frequency) equal to the number of transmitter antennas. The study of the system considers a comparative performance analysis of di erent ST, SF and STF codes. The simulations of the system were performed on a triply selective block fading channel. Thus, there was selectivity in the fading over time, space and frequency. The effect of quantisation at the receiver on the achievable diversity of linearly pre-coded systems (such as the STF codes used) was mathematically derived and verified with simulations. A sphere decoder (SD) was used as a MIMO detector. The standard method used to create a soft-input soft output (SISO) SD uses a hard-to-soft process and the max-log-map approximation. A new approach was developed which combines a Hopfield network with the SD. This SD-Hopfield detector was connected with the fast Fourier transform belief propagation (FFT-BP) algorithm in an iterative structure. This iterative system was able to achieve the same bit error rate (BER) performance as the original SISO-SD at a reduced complexity. The use of the iterative Hopfield-SD and FFT-BP decoder system also allows performance to be traded off for complexity by varying the number of decoding iterations. The complete system employs a NB-LDPC code concatenated with an STF code at the transmitter with a SISO-SD and FFT-BP decoder connected in an iterative structure at the receiver. The system was analysed in varying channel conditions taking into account the effect of correlation and quantisation. The performance of different SF and STF codes were compared and analysed in the system. An analysis comparing different numbers of FFT-BP and outer iterations was also done. AFRIKAANS : Die doel van die verhandeling was om ’n realistiese, lae-kompleksiteit nie-binˆere (NB) LDPC gekodeerde ruimte-tyd-frekwensie-gekodeerde MIMO-OFDM-sisteem met iteratiewe gesamentlike dekodeerder- en detektorstrukture by die ontvanger te ontwerp. Die eerstem deel van die verhandeling was om die werkverrigting van verskillende ontwerpprosedures vir NB-LDPC kodes op ’n gesommeerde wit Gausruiskanaal te vergelyk met inagneming van die beperking op die lengte van die kode. Verskillende metodes om die nie-bineêre elemente in die pariteitstoetsmatriks te kies, is gebruik. Vir die ruimte-tyd-frekwensiekodering is ’n klas universele ruimte-tyd-frekwensiekodes gebruik. Hierdie kodes gebruik lineêre pre-kodering en ’n laagbenadering gebaseer op Diofantiese syfers om volle diversiteit te bereik en ’n oordragtempo (in simbole per kanaalgebruik per frekwensie) gelyk aan die aantal senderantennes. Die studie van die sisteem oorweeg ’n vergelykende werkverrigtinganalisie van verskillende ruimte-tyd-, ruimte-freksensie- en ruimte-tyd-frekwensiekodes. Die simulasies van die sisteem is gedoen op ’n drievoudig selektiewe blokwegsterwingskanaal. Daar was dus selektiwiteit in die wegsterwing oor tyd, ruimte en frekwensie. Die effek van kwantisering by die ontvanger op die bereikbare diversiteit van lineêr pre-gekodeerde sisteme (soos die ruimte-tyd-frekwensiekodes wat gebruik is) is matematies afgelei en bevestig deur simulasies. ’n Sfeerdekodeerder (SD) is gebruik as ’n MIMO-detektor. Die standaardmetode wat gebuik is om ’n sagte-inset-sagte-uitset (SISO) SD te skep, gebruik ’n harde-na-sagte proses en die maksimum logaritmiese afbeelding-benadering. ’n Nuwe benadering wat ’n Hopfield-netwerk met die SD kombineer, is ontwikkel. Hierdie SD-Hopfield-detektor is verbind met die FFT-BP-algoritme in iteratiewe strukture. Hierdie iteratiewe sisteem was in staat om dieselfde bisfouttempo te bereik as die oorspronklike SISO-SD, met laer kompleksiteit. Die gebruik van die iteratiewe Hopfield-SD en FFT-BP-dekodeerdersisteem maak ook daarvoor voorsiening dat werkverrigting opgeweeg kan word teen kompleksiteit deur die aantal dekodering-iterasies te varieer. Die volledige sisteem maak gebruik van ’n QC-NB-LDPC-kode wat met ’n ruimte-tyd-frekwensiekode by die sender aaneengeskakel is met ’n SISO-SD en FFT-BP-dekodeerder wat in ’n iteratiewe struktuur by die ontvanger gekoppel is. Die sisteem is onder ’n verskeidenheid kanaalkondisies ge-analiseer met inagneming van die effek van korrelasie en kwantisering. Die werkverrigting van verskillende ruimte-frekwensie- en ruimte-tyd-frekwensiekodes is vergelyk en in die sisteem ge-analiseer. ’n Analise om ’n wisselende aantal FFT-BP en buite-iterasies te vergelyk, is ook gedoen. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Electrical, Electronic and Computer Engineering / unrestricted

The search for the closest lattice point arises in many communication problems, and is known to be NP-hard. The Maximum Likelihood (ML) Detector is the optimal detector which yields an optimal solution to this problem, but at the expense of high computational complexity. Existing near-optimal methods used to solve the problem are based on the Sphere Decoder (SD), which searches for lattice points confined in a hyper-sphere around the received point. The SD has emerged as a powerful means of finding the solution to the ML detection problem for MIMO systems. However the bottleneck lies in the determination of the initial radius. This thesis is concerned with the detection of transmitted wireless signals in Multiple-Input Multiple-Output (MIMO) digital communication systems as efficiently and effectively as possible. The main objective of this thesis is to design efficient ML detection algorithms for MIMO systems based on the depth-first search (DFS) algorithms whilst taking into account complexity and bit error rate performance requirements for advanced digital communication systems. The increased capacity and improved link reliability of MIMO systems without sacrificing bandwidth efficiency and transmit power will serve as the key motivation behind the study of MIMO detection schemes. The fundamental principles behind MIMO systems are explored in Chapter 2. A generic framework for linear and non-linear tree search based detection schemes is then presented Chapter 3. This paves way for different methods of improving the achievable performance-complexity trade-off for all SD-based detection algorithms. The suboptimal detection schemes, in particular the Minimum Mean Squared Error-Successive Interference Cancellation (MMSE-SIC), will also serve as pre-processing as well as comparison techniques whilst channel capacity approaching Low Density Parity Check (LDPC) codes will be employed to evaluate the performance of the proposed SD. Numerical and simulation results show that non-linear detection schemes yield better performance compared to linear detection schemes, however, at the expense of a slight increase in complexity. The first contribution in this thesis is the design of a near ML-achieving SD algorithm for MIMO digital communication systems that reduces the number of search operations within the sphere-constrained search space at reduced detection complexity in Chapter 4. In this design, the distance between the ML estimate and the received signal is used to control the lower and upper bound radii of the proposed SD to prevent NP-complete problems. The detection method is based on the DFS algorithm and the Successive Interference Cancellation (SIC). The SIC ensures that the effects of dominant signals are effectively removed. Simulation results presented in this thesis show that by employing pre-processing detection schemes, the complexity of the proposed SD can be significantly reduced, though at marginal performance penalty. The second contribution is the determination of the initial sphere radius in Chapter 5. The new initial radius proposed in this thesis is based on the variable parameter α which is commonly based on experience and is chosen to ensure that at least a lattice point exists inside the sphere with high probability. Using the variable parameter α, a new noise covariance matrix which incorporates the number of transmit antennas, the energy of the transmitted symbols and the channel matrix is defined. The new covariance matrix is then incorporated into the EMMSE model to generate an improved EMMSE estimate. The EMMSE radius is finally found by computing the distance between the sphere centre and the improved EMMSE estimate. This distance can be fine-tuned by varying the variable parameter α. The beauty of the proposed method is that it reduces the complexity of the preprocessing step of the EMMSE to that of the Zero-Forcing (ZF) detector without significant performance degradation of the SD, particularly at low Signal-to-Noise Ratios (SNR). More specifically, it will be shown through simulation results that using the EMMSE preprocessing step will substantially improve performance whenever the complexity of the tree search is fixed or upper bounded. The final contribution is the design of the LRAD-MMSE-SIC based SD detection scheme which introduces a trade-off between performance and increased computational complexity in Chapter 6. The Lenstra-Lenstra-Lovasz (LLL) algorithm will be utilised to orthogonalise the channel matrix H to a new near orthogonal channel matrix H ̅.The increased computational complexity introduced by the LLL algorithm will be significantly decreased by employing sorted QR decomposition of the transformed channel H ̅ into a unitary matrix and an upper triangular matrix which retains the property of the channel matrix. The SIC algorithm will ensure that the interference due to dominant signals will be minimised while the LDPC will effectively stop the propagation of errors within the entire system. Through simulations, it will be demonstrated that the proposed detector still approaches the ML performance while requiring much lower complexity compared to the conventional SD.

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. / 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.