It is know that the LORD (Layered Orthogonal Lattice Detector) and the sphere decoding achieve performance equaling that of ML. However, both detectors have different disadvantage. When the transmit antenna number is greater than three antennas, it is difficult to apply the LORD. Therefore, we consider using the sphere decoding together with the LORD. The complexity of the sphere decoding highly depends on the initial radius. In this thesis, we intend to reduce the sphere decoding complexity by using LORD.

Multiple Input Multiple Output (MIMO) systems are a key technology for next generation high speed wireless communication standards like 802.11n, WiMax etc. MIMO enables spatial multiplexing to increase channel bandwidth which requires the use of multiple antennas in the receiver and transmitter side. The increase in bandwidth comes at the cost of high silicon complexity of MIMO detectors which result, due to the intricate algorithms required for the separation of these spatially multiplexed streams. Previous implementations of MIMO detector have mainly dealt with the issue of complexity reduction, latency minimization and throughput enhancement. Although, these detectors have successfully mapped algorithms to relatively simpler circuits but still, latency and throughput of these systems need further improvements to meet standard requirements. Additionally, most of these implementations don’t deal with the requirements of reconfigurability of the detector to multiple modulation schemes and different antennae configurations. This necessary requirement provides another dimension to the implementation of MIMO detector and adds to the implementation complexity. This thesis focuses on the efficient VLSI implementation of the MIMO detector with an emphasis on performance and re-configurability to different modulation schemes. MIMO decoding in our detector is based on the fixed sphere decoding algorithm which has been simplified for an effective VLSI implementation without considerably degrading the near optimal bit error rate performance. The regularity of the architecture makes it suitable for a highly parallel and pipelined implementation. The decoder has intrinsic traits for dynamic re-configurability to different modulation and encoding schemes. This detector architecture can be easily tuned for high/low performance requirements with slight degradation/improvement in Bit Error Rate (BER) depending on needs of the overlying application. Additionally, various architectural optimizations like pipelining, parallel processing, hardware scheduling, dynamic voltage and frequency scaling have been explored to improve the performance, energy requirements and re-configurability of the design.

Multiple-input multiple-output (MIMO) is a well-known technique for efficiently increasing bandwidth utilization. However, the implementation of the MIMO receiver with a reasonable hardware cost is a big challenge. Most MIMO receivers exploit minimum mean-square error (MMSE), zero-forcing (ZF) and maximum-likelihood (ML) to detect MIMO signals. Among the detectors, the ZF detector is simple detector with low computational complexity, but lower performance compared to ML decoder, which has huge computational complexity. If the K-Best sphere decoding algorithm (SDA) is adopted, the system complexity can be substantially reduced and the performance can approach that of the ML scheme when the value K is sufficiently large. In this paper, a hard-output MIMO detector is implemented using the K-Best SDA for 4¡Ñ4 64-quadrature amplitude modulation (QAM) MIMO detection. The implementation is realized by using a 0.18-£gm CMOS technology. The implementation chip core area is 3.35mm2 with 229K gates, and the decoding throughput is up to 3.12Mb/s with a 25MHz clock rate.

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 sistemas / Roger 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/10251/16562 / Palancia

This thesis fits into the Multiple-Input Multiple-Output (MIMO) communication systems. Nowadays, these schemes are the most promising technology in the field of wireless communications. The use of this technology allows to increase the rate and the quality of the transmission through the use of multiple antennas at the transmitter and receiver sides. Furthermore, the MIMO technology can also be used in a multiuser scenario, where a Base Station (BS) equipped with several antennas serves several users that share the spatial dimension causing interference. However, employing precoding algorithms the signal of the multiuser interference can be mitigated. For these reasons, the MIMO technology has become an essential key in many new generation communications standards. On the other hand, Massive MIMO technology or Large MIMO, where the BS is equipped with very large number of antennas (hundreds or thousands) serves many users in the same time-frequency resource. Nevertheless, the advantages provided by the MIMO technology entail a substantial increase in the computational cost. Therefore the design of low-complexity receivers is an important issue which is tackled throughout this thesis. To this end, one of the main contributions of this dissertation is the implementation of efficient soft-output detectors and precoding schemes. First, the problem of efficient soft detection with no iteration at the receiver has been addressed. A detailed overview of the most employed soft detectors is provided. Furthermore, the complexity and performance of these methods are evaluated and compared. Additionally, two low-complexity algorithms have been proposed. The first algorithm is based on the efficient Box Optimization Hard Detector (BOHD) algorithm and provides a low-complexity implementation achieving a suitable performance. The second algorithm tries to reduce the computational cost of the Subspace Marginalization with Interference Suppression (SUMIS) algorithm. Second, soft-input soft-output (SISO) detectors, which are included in an iterative receiver structure, have been investigated. An iterative receiver improves the performance with respect to no iteration, achieving a performance close to the channel capacity. In contrast, its computational cost becomes prohibitive. In this context, three algorithms are presented. Two of them achieve max-log performance reducing the complexity of standard SISO detectors. The last one achieves near max-log performance with low complexity. The precoding problem has been addressed in the third part of this thesis. An analysis of some of the most employed precoding techniques has been carried out. The algorithms have been compared in terms of performance and complexity. In this context, the impact of the channel matrix condition number on the performance of the precoders has been analyzed. This impact has been exploited to propose an hybrid precoding scheme that reduces the complexity of the previously proposed precoders. In addition, in Large MIMO systems, an alternative precoder scheme is proposed. In the last part of the thesis, parallel implementations of the SUMIS algorithm are presented. Several strategies for the parallelization of the algorithm are proposed and evaluated on two different platforms: multicore central processing unit (CPU) and graphics processing unit (GPU). The parallel implementations achieve a significant speedup compared to the CPU version. Therefore, these implementations allow to simulate a scalable quasi optimal soft detector in a Large MIMO system much faster than by conventional simu / La presente tesis se enmarca dentro de los sistemas de comunicaciones de múltiples antenas o sistemas MIMO. Hoy en día, estos sistemas presentan una de las tecnologías más prometedoras dentro de los sistemas comunicaciones inalámbricas. A través del uso de múltiples antenas en ambos lados, transmisor y receptor, la tasa de transmisión y la calidad de la misma es aumentada. Por otro lado, la tecnología MIMO puede ser utilizada en un escenario multiusuario, donde una estación base (BS) la cual está equipada con varias antenas, sirve a varios usuarios al mismo tiempo, estos usuarios comparten dimensión espacial causando interferencias multiusuario. Por todas estas razones, la tecnología MIMO ha sido adoptada en muchos de los estándares de comunicaciones de nueva generación. Por otro lado, la tecnología MIMO Masivo, en la cual la estación base está equipada con un gran número de antenas (cientos o miles) que sirve a muchos usuarios en el mismo recurso de tiempo-frecuencia. Sin embargo, las ventajas proporcionadas por los sistemas MIMO implican un aumento en el coste computacional requerido. Por ello, el diseño de receptores de baja complejidad es una cuestión importante en estos sistemas. Para conseguir esta finalidad, las principales contribuciones de la tesis se basan en la implementación de algoritmos de detección soft y esquemas de precodificación eficientes. En primer lugar, el problema de la detección soft eficiente en un sistema receptor sin iteración es abordado. Una descripción detallada sobre los detectores soft más empleados es presentada. Por otro lado, han sido propuestos dos algoritmos de bajo coste. El primer algoritmo está basado en el algoritmo Box Optimization Hard Detector (BOHD) y proporciona una baja complejidad de implementación logrando un buen rendimiento. El segundo de los algoritmos propuestos intenta reducir el coste computacional del conocido algoritmo Subspace Marginalization with Interference Suppression (SUMIS). En segundo lugar, han sido investidados detectores de entrada y salida soft (SISO, soft-input soft-output) los cuales son ejecutados en estructuras de recepción iterativa. El empleo de un receptor iterativo mejora el rendimiento del sistema con respecto a no realizar realimentación, pudiendo lograr la capacidad óptima. Por el contrario, el coste computacional se vuelve prohibitivo. En este contexto, tres algoritmos han sido presentados. Dos de ellos logran un rendimiento óptimo, reduciendo la complejidad de los detectores SISO óptimos que normalmente son empleados. Por el contrario, el otro algoritmo logra un rendimiento casi óptimo a baja complejidad. En la tercera parte, se ha abordado el problema de la precodificación. Se ha llevado a cabo un análisis de algunas de las técnicas de precodificación más usadas. En este contexto, se ha evaluado el impacto que el número de condición de la matriz de canal tiene en el rendimiento de los precodificadores. Además, se ha aprovechado este impacto para proponer un precodificador hibrido. Por otro lado, en MIMO Masivo, se ha propuesto un esquema precodificador. En la última parte de la tesis, la implementación paralela del algoritmo SUMIS es presentada. Varias estrategias sobre la paralelización del algoritmo han sido propuestas y evaluadas en dos plataformas diferentes: Unidad Central de Procesamiento multicore (multicore CPU) y Unidad de Procesamiento Gráfico (GPU). Las implementaciones paralelas consiguen una mejora de speedup. Estas implementaciones permiten simular para MIMO Masivo y de forma más rápida que por simulación convencional, un algo / La present tesi s'emmarca dins dels sistemes de comunicacions de múltiples antenes o sistemes MIMO. Avui dia, aquestos sistemes presenten una de les tecnologies més prometedora dins dels sistemes de comunicacions inalàmbriques. A través de l'ús de múltiples antenes en tots dos costats, transmissor y receptor, es pot augmentar la taxa de transmissió i la qualitat de la mateixa. D'altra banda, la tecnologia MIMO es pot utilitzar en un escenari multiusuari, on una estació base (BS) la qual està equipada amb diverses antenes serveix a diversos usuaris al mateix temps, aquests usuaris comparteixen dimensió espacial causant interferències multiusuari. Per totes aquestes raons, la tecnologia MIMO ha sigut adoptada en molts dels estàndars de comunicacions de nova generació. D'altra banda, la tecnologia MIMO Massiu, en la qual l'estació base està equipada amb un gran nombre d'antenes (centenars o milers) que serveix a molts usuaris en el mateix recurs de temps-freqüència. No obstant això, els avantatges proporcionats pels sistemes MIMO impliquen un augment en el cost computacional requerit. Per això, el disseny de receptors de baixa complexitat és una qüestió important en aquests sistemes. Per tal d'aconseguir esta finalitat, les principals contribucions de la tesi es basen en la implementació d'algoritmes de detecció soft i esquemes de precodificació eficients. En primer lloc, és abordat el problema de la detecció soft eficient en un sistema receptor sense interacció. Una descripció detallada dels detectors soft més emprats és presentada. D'altra banda, han sigut proposats dos algorismes de baix cost. El primer algorisme està basat en l'algorisme Box Optimization Hard Decoder (BOHD) i proporciona una baixa complexitat d'implementació aconseguint un bon resultat. El segon dels algorismes proposats intenta reduir el cost computacional del conegut algoritme Subspace Marginalization with Interference Suppression (SUMIS). En segon lloc, detectors d'entrada i eixidia soft (SISO, soft-input soft-output) els cuals són executats en estructures de recepció iterativa han sigut investigats. L'ocupació d'un receptor iteratiu millora el rendiment del sistema pel que fa a no realitzar realimentació, podent aconseguir la capacitat òptima. Per contra, el cost computacional es torna prohibitiu. En aquest context, tres algorismes han sigut presentats. Dos d'ells aconsegueixen un rendiment òptim, reduint la complexitat dels detectors SISO òptims que normalment són emprats. Per contra, l'altre algorisme aconsegueix un rendiment quasi òptim a baixa complexitat. En la tercera part, s'ha abordat el problema de la precodificació. S'ha dut a terme una anàlisi d'algunes de les tècniques de precodificació més usades, prestant especial atenció al seu rendiment i a la seua complexitat. Dins d'aquest context, l'impacte que el nombre de condició de la matriu de canal té en el rendiment dels precodificadors ha sigut avaluat. A més, aquest impacte ha sigut aprofitat per a proposar un precodificador híbrid , amb la finalitat de reduir la complexitat d'algorismes prèviament proposats. D'altra banda, en MIMO Massiu, un esquema precodificador ha sigut proposat. En l'última part, la implementació paral·lela de l'algorisme SUMIS és presentada. Diverses estratègies sobre la paral·lelizació de l'algorisme han sigut proposades i avaluades en dues plataformes diferents: multicore CPU i GPU. Les implementacions paral·leles aconsegueixen una millora de speedup quan el nombre d'àntenes o l'ordre de la constel·lació incrementen. D'aquesta manera, aquestes implementacions permeten simular per a MIMO Massiu, i de forma més ràpida que la simulació convencional. / Simarro Haro, MDLA. (2017). Effi cient algorithms for iterative detection and decoding in Multiple-Input and Multiple-Output Communication Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86186 / TESIS

The theory of lattices --- a mathematical approach for representing infinite discrete points in Euclidean space, has become a powerful tool to analyze many point-to-point digital and wireless communication systems, particularly, communication systems that can be well-described by the linear Gaussian vector channel model. This is mainly due to the three facts about channel codes constructed using lattices: they have simple structure, their ability to achieve the fundamental limits (the capacity) of the channel, and most importantly, they can be decoded using efficient decoders called lattice decoders. Since its introduction to multiple-input multiple-output (MIMO) wireless communication systems, sphere decoders has become an attractive efficient implementation of lattice decoders, especially for small signal dimensions and/or moderate to large signal-to-noise ratios (SNRs). In the first part of this dissertation, we consider sphere decoding algorithms that describe lattice decoding. The exact complexity analysis of the basic sphere decoder for general space-time codes applied to MIMO wireless channel is known to be difficult. Characterizing and understanding the complexity distribution is important, especially when the sphere decoder is used under practically relevant runtime constraints. In this work, we shed the light on the (average) computational complexity of sphere decoding for the quasi-static, LAttice Space-Time (LAST) coded MIMO channel. Sphere decoders are only efficient in the high SNR regime and low signal dimensions, and exhibits exponential (average) complexity for low-to-moderate SNR and large signal dimensions. On the other extreme, linear and non-linear receivers such as minimum mean-square error (MMSE), and MMSE decision-feedback equalization (DFE) are considered attractive alternatives to sphere decoders in MIMO channels. Unfortunately, the very low decoding complexity advantage that these decoders can provide comes at the expense of poor performance, especially for large signal dimensions. The problem of designing low complexity receivers for the MIMO channel that achieve near-optimal performance is considered a challenging problem and has driven much research in the past years. The problem can solved through the use of lattice sequential decoding that is capable of bridging the gap between sphere decoders and low complexity linear decoders (e.g., MMSE-DFE decoder). In the second part of this thesis, the asymptotic performance of the lattice sequential decoder for LAST coded MIMO channel is analyzed. We determine the rates achievable by lattice coding and sequential decoding applied to such a channel. The diversity-multiplexing tradeoff under such a decoder is derived as a function of its parameter--- the bias term. In this work, we analyze both the computational complexity distribution and the average complexity of such a decoder in the high SNR regime. We show that there exists a cut-off multiplexing gain for which the average computational complexity of the decoder remains bounded. Our analysis reveals that there exists a finite probability that the number of computations performed by the decoder may become excessive, even at high SNR, during high channel noise. This probability is usually referred to as the probability of a decoding failure. Such probability limits the performance of the lattice sequential decoder, especially for a one-way communication system. For a two-way communication system, such as in MIMO Automatic Repeat reQuest (ARQ) system, the feedback channel can be used to eliminate the decoding failure probability. In this work, we modify the lattice sequential decoder for the MIMO ARQ channel, to predict in advance the occurrence of decoding failure to avoid wasting the time trying to decode the message. This would result in a huge saving in decoding complexity. In particular, we will study the throughput-performance-complexity tradeoffs in sequential decoding algorithms and the effect of preprocessing and termination strategies. We show, analytically and via simulation, that using the lattice sequential decoder that implements a simple yet efficient time-out algorithm for joint error detection and correction, the optimal tradeoff of the MIMO ARQ channel can be achieved with significant reduction in decoding complexity.

In this thesis, we consider the problem of designing space-time block codes that have low maximum-likelihood (ML) decoding complexity. We present a unified framework for determining the worst-case ML decoding complexity of space-time block codes. We use this framework to not only determine the worst-case ML decoding complexity of our own constructions, but also to show that some popular constructions of space-time block codes have lower ML decoding complexity than was previously known. Recognizing the practical importance of the two transmit and two receive antenna system, we propose the asymmetric golden code, which is designed specifically for low ML decoding complexity. The asymmetric golden code has the lowest decoding complexity compared to previous constructions of space-time codes, regardless of whether the channel varies with time. We also propose the embedded orthogonal space-time codes, which is a family of codes for an arbitrary number of antennas, and for any rate up to half the number of antennas. The family of embedded orthogonal space-time codes is the first general framework for the construction of space-time codes with low-complexity decoding, not only for rate one, but for any rate up to half the number of transmit antennas. Simulation results for up to six transmit antennas show that the embedded orthogonal space-time codes are simultaneously lower in complexity and lower in error probability when compared to some of the most important constructions of space-time block codes with the same number of antennas and the same rate larger than one. Having considered the design of space-time block codes with low ML decoding complexity on the transmitter side, we also develop efficient algorithms for ML decoding for the golden code, the asymmetric golden code and the embedded orthogonal space-time block codes on the receiver side. Simulations of the bit-error rate performance and decoding complexity of the asymmetric golden code and embedded orthogonal codes are used to demonstrate their attractive performance-complexity tradeoff.

The theory of lattices --- a mathematical approach for representing infinite discrete points in Euclidean space, has become a powerful tool to analyze many point-to-point digital and wireless communication systems, particularly, communication systems that can be well-described by the linear Gaussian vector channel model. This is mainly due to the three facts about channel codes constructed using lattices: they have simple structure, their ability to achieve the fundamental limits (the capacity) of the channel, and most importantly, they can be decoded using efficient decoders called lattice decoders. Since its introduction to multiple-input multiple-output (MIMO) wireless communication systems, sphere decoders has become an attractive efficient implementation of lattice decoders, especially for small signal dimensions and/or moderate to large signal-to-noise ratios (SNRs). In the first part of this dissertation, we consider sphere decoding algorithms that describe lattice decoding. The exact complexity analysis of the basic sphere decoder for general space-time codes applied to MIMO wireless channel is known to be difficult. Characterizing and understanding the complexity distribution is important, especially when the sphere decoder is used under practically relevant runtime constraints. In this work, we shed the light on the (average) computational complexity of sphere decoding for the quasi-static, LAttice Space-Time (LAST) coded MIMO channel. Sphere decoders are only efficient in the high SNR regime and low signal dimensions, and exhibits exponential (average) complexity for low-to-moderate SNR and large signal dimensions. On the other extreme, linear and non-linear receivers such as minimum mean-square error (MMSE), and MMSE decision-feedback equalization (DFE) are considered attractive alternatives to sphere decoders in MIMO channels. Unfortunately, the very low decoding complexity advantage that these decoders can provide comes at the expense of poor performance, especially for large signal dimensions. The problem of designing low complexity receivers for the MIMO channel that achieve near-optimal performance is considered a challenging problem and has driven much research in the past years. The problem can solved through the use of lattice sequential decoding that is capable of bridging the gap between sphere decoders and low complexity linear decoders (e.g., MMSE-DFE decoder). In the second part of this thesis, the asymptotic performance of the lattice sequential decoder for LAST coded MIMO channel is analyzed. We determine the rates achievable by lattice coding and sequential decoding applied to such a channel. The diversity-multiplexing tradeoff under such a decoder is derived as a function of its parameter--- the bias term. In this work, we analyze both the computational complexity distribution and the average complexity of such a decoder in the high SNR regime. We show that there exists a cut-off multiplexing gain for which the average computational complexity of the decoder remains bounded. Our analysis reveals that there exists a finite probability that the number of computations performed by the decoder may become excessive, even at high SNR, during high channel noise. This probability is usually referred to as the probability of a decoding failure. Such probability limits the performance of the lattice sequential decoder, especially for a one-way communication system. For a two-way communication system, such as in MIMO Automatic Repeat reQuest (ARQ) system, the feedback channel can be used to eliminate the decoding failure probability. In this work, we modify the lattice sequential decoder for the MIMO ARQ channel, to predict in advance the occurrence of decoding failure to avoid wasting the time trying to decode the message. This would result in a huge saving in decoding complexity. In particular, we will study the throughput-performance-complexity tradeoffs in sequential decoding algorithms and the effect of preprocessing and termination strategies. We show, analytically and via simulation, that using the lattice sequential decoder that implements a simple yet efficient time-out algorithm for joint error detection and correction, the optimal tradeoff of the MIMO ARQ channel can be achieved with significant reduction in decoding complexity.

[EN] Nowadays, several communication standards are emerging and evolving, searching higher transmission rates, reliability and coverage. This expansion is primarily driven by the continued increase in consumption of mobile multimedia services due to the emergence of new handheld devices such as smartphones and tablets. One of the most significant techniques employed to meet these demands is the use of multiple transmit and receive antennas, known as MIMO systems. The use of this technology allows to increase the transmission rate and the quality of the transmission through the use of multiple antennas at the transmitter and receiver sides. MIMO technologies have become an essential key in several wireless standards such as WLAN, WiMAX and LTE. These technologies will be incorporated also in future standards, therefore is expected in the coming years a great deal of research in this field. Clearly, the study of MIMO systems is critical in the current investigation, however the problems that arise from this technology are very complex. High Performance Computing (HPC) systems, and specifically, modern hardware architectures as multi-core and many-cores (e.g Graphics Processing Units (GPU)) are playing a key role in the development of efficient and low-complexity algorithms for MIMO transmissions. Proof of this is that the number of scientific contributions and research projects related to its use has increased in the last years. Also, some high performance libraries have been implemented as tools for researchers involved in the development of future communication standards. Two of the most popular libraries are: IT++ that is a library based on the use of some optimized libraries for multi-core processors and the Communications System Toolbox designed for use with MATLAB, which uses GPU computing. However, there is not a library able to run on a heterogeneous platform using all the available resources. In view of the high computational requirements in MIMO application research and the shortage of tools able to satisfy them, we have made a special effort to develop a library to ease the development of adaptable parallel applications in accordance with the different architectures of the executing platform. The library, called MIMOPack, aims to implement efficiently using parallel computing, a set of functions to perform some of the critical stages of MIMO communication systems simulation. The main contribution of the thesis is the implementation of efficient Hard and Soft output detectors, since the detection stage is considered the most complex part of the communication process. These detectors are highly configurable and many of them include preprocessing techniques that reduce the computational cost and increase the performance. The proposed library shows three important features: portability, efficiency and easy of use. Current realease allows GPUs and multi-core computation, or even simultaneously, since it is designed to use on heterogeneous machines. The interface of the functions are common to all environments in order to simplify the use of the library. Moreover, some of the functions are callable from MATLAB increasing the portability of developed codes between different computing environments. According to the library design and the performance assessment, we consider that MIMOPack may facilitate industrial and academic researchers the implementation of scientific codes without having to know different programming languages and machine architectures. This will allow to include more complex algorithms in their simulations and obtain their results faster. This is particularly important in the industry, since the manufacturers work to analyze and to propose their own technologies with the aim that it will be approved as a standard. Thus allowing to enforce their intellectual property rights over their competitors, who should obtain the corresponding licenses to include these technologies into their products. / [ES] En la actualidad varios estándares de comunicación están surgiendo buscando velocidades de transmisión más altas y mayor fiabilidad. Esta expansión está impulsada por el aumento en el consumo de servicios multimedia debido a la aparición de nuevos dispositivos como los smartphones y las tabletas. Una de las técnicas empleadas más importantes es el uso de múltiples antenas de transmisión y recepción, conocida como sistemas MIMO, que permite aumentar la velocidad y la calidad de la transmisión. Las tecnologías MIMO se han convertido en una parte esencial en diferentes estándares tales como WLAN, WiMAX y LTE. Estas tecnologías se incorporarán también en futuros estándares, por lo tanto, se espera en los próximos años una gran cantidad de investigación en este campo. Está claro que el estudio de los sistemas MIMO es crítico en la investigación actual, sin embargo los problemas que surgen de esta tecnología son muy complejos. La sistemas de computación de alto rendimiento, y en concreto, las arquitecturas hardware actuales como multi-core y many-core (p. ej. GPUs) están jugando un papel clave en el desarrollo de algoritmos eficientes y de baja complejidad en las transmisiones MIMO. Prueba de ello es que el número de contribuciones científicas y proyectos de investigación relacionados con su uso se han incrementado en el últimos años. Algunas librerías de alto rendimiento se están utilizando como herramientas por investigadores en el desarrollo de futuros estándares. Dos de las librerías más destacadas son: IT++ que se basa en el uso de distintas librerías optimizadas para procesadores multi-core y el paquete Communications System Toolbox diseñada para su uso con MATLAB, que utiliza computación con GPU. Sin embargo, no hay una biblioteca capaz de ejecutarse en una plataforma heterogénea. En vista de los altos requisitos computacionales en la investigación MIMO y la escasez de herramientas capaces de satisfacerlos, hemos implementado una librería que facilita el desarrollo de aplicaciones paralelas adaptables de acuerdo con las diferentes arquitecturas de la plataforma de ejecución. La librería, llamada MIMOPack, implementa de manera eficiente un conjunto de funciones para llevar a cabo algunas de las etapas críticas en la simulación de un sistema de comunicación MIMO. La principal aportación de la tesis es la implementación de detectores eficientes de salida Hard y Soft, ya que la etapa de detección es considerada la parte más compleja en el proceso de comunicación. Estos detectores son altamente configurables y muchos de ellos incluyen técnicas de preprocesamiento que reducen el coste computacional y aumentan el rendimiento. La librería propuesta tiene tres características importantes: la portabilidad, la eficiencia y facilidad de uso. La versión actual permite computación en GPU y multi-core, incluso simultáneamente, ya que está diseñada para ser utilizada sobre plataformas heterogéneas que explotan toda la capacidad computacional. Para facilitar el uso de la biblioteca, las interfaces de las funciones son comunes para todas las arquitecturas. Algunas de las funciones se pueden llamar desde MATLAB aumentando la portabilidad de códigos desarrollados entre los diferentes entornos. De acuerdo con el diseño de la biblioteca y la evaluación del rendimiento, consideramos que MIMOPack puede facilitar la implementación de códigos sin tener que saber programar con diferentes lenguajes y arquitecturas. MIMOPack permitirá incluir algoritmos más complejos en las simulaciones y obtener los resultados más rápidamente. Esto es particularmente importante en la industria, ya que los fabricantes trabajan para proponer sus propias tecnologías lo antes posible con el objetivo de que sean aprobadas como un estándar. De este modo, los fabricantes pueden hacer valer sus derechos de propiedad intelectual frente a sus competidores, quienes luego deben obtener las correspon / [CA] En l'actualitat diversos estàndards de comunicació estan sorgint i evolucionant cercant velocitats de transmissió més altes i major fiabilitat. Aquesta expansió, està impulsada pel continu augment en el consum de serveis multimèdia a causa de l'aparició de nous dispositius portàtils com els smartphones i les tablets. Una de les tècniques més importants és l'ús de múltiples antenes de transmissió i recepció (MIMO) que permet augmentar la velocitat de transmissió i la qualitat de transmissió. Les tecnologies MIMO s'han convertit en una part essencial en diferents estàndards inalàmbrics, tals com WLAN, WiMAX i LTE. Aquestes tecnologies s'incorporaran també en futurs estàndards, per tant, s'espera en els pròxims anys una gran quantitat d'investigació en aquest camp. L'estudi dels sistemes MIMO és crític en la recerca actual, no obstant açó, els problemes que sorgeixen d'aquesta tecnologia són molt complexos. Els sistemes de computació d'alt rendiment com els multi-core i many-core (p. ej. GPUs)), estan jugant un paper clau en el desenvolupament d'algoritmes eficients i de baixa complexitat en les transmissions MIMO. Prova d'açò és que el nombre de contribucions científiques i projectes d'investigació relacionats amb el seu ús s'han incrementat en els últims anys. Algunes llibreries d'alt rendiment estan utilitzant-se com a eines per investigadors involucrats en el desenvolupament de futurs estàndards. Dos de les llibreries més destacades són: IT++ que és una llibreria basada en lús de diferents llibreries optimitzades per a processadors multi-core i el paquet Communications System Toolbox dissenyat per al seu ús amb MATLAB, que utilitza computació amb GPU. No obstant açò, no hi ha una biblioteca capaç d'executar-se en una plataforma heterogènia. Degut als alts requisits computacionals en la investigació MIMO i l'escacès d'eines capaces de satisfer-los, hem implementat una llibreria que facilita el desenvolupament d'aplicacions paral·leles adaptables d'acord amb les diferentes arquitectures de la plataforma d'ejecució. La llibreria, anomenada MIMOPack, implementa de manera eficient, un conjunt de funcions per dur a terme algunes de les etapes crítiques en la simulació d'un sistema de comunicació MIMO. La principal aportació de la tesi és la implementació de detectors eficients d'exida Hard i Soft, ja que l'etapa de detecció és considerada la part més complexa en el procés de comunicació. Estos detectors són altament configurables i molts d'ells inclouen tècniques de preprocessament que redueixen el cost computacional i augmenten el rendiment. La llibreria proposta té tres característiques importants: la portabilitat, l'eficiència i la facilitat d'ús. La versió actual permet computació en GPU i multi-core, fins i tot simultàniament, ja que està dissenyada per a ser utilitzada sobre plataformes heterogènies que exploten tota la capacitat computacional. Amb el fi de simplificar l'ús de la biblioteca, les interfaces de les funcions són comunes per a totes les arquitectures. Algunes de les funcions poden ser utilitzades des de MATLAB augmentant la portabilitat de còdics desenvolupats entre els diferentes entorns. D'acord amb el disseny de la biblioteca i l'evaluació del rendiment, considerem que MIMOPack pot facilitar la implementació de còdics a investigadors sense haver de saber programar amb diferents llenguatges i arquitectures. MIMOPack permetrà incloure algoritmes més complexos en les seues simulacions i obtindre els seus resultats més ràpid. Açò és particularment important en la industria, ja que els fabricants treballen per a proposar les seues pròpies tecnologies el més prompte possible amb l'objectiu que siguen aprovades com un estàndard. D'aquesta menera, els fabricants podran fer valdre els seus drets de propietat intel·lectual enfront dels seus competidors, els qui després han d'obtenir les corresponents llicències si vole / Ramiro Sánchez, C. (2015). MIMOPack: A High Performance Computing Library for MIMO Communication Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/53930 / TESIS / Premios Extraordinarios de tesis doctorales

One of the most popular ways to exploit the advantages of a multiple-input multiple-output (MIMO) system is using space time block coding. A space time block code (STBC) is a finite set of complex matrices whose entries consist of the information symbols to be transmitted. A linear STBC is one in which the information symbols are linearly combined to form a two-dimensional code matrix. A well known method of maximum-likelihood (ML) decoding of such STBCs is using the sphere decoder (SD). In this thesis, new constructions of STBCs with low sphere decoding complexity are presented and various ways of characterizing and reducing the sphere decoding complexity of an STBC are addressed. The construction of low sphere decoding complexity STBCs is tackled using irreducible matrix representations of Clifford algebras, cyclic division algebras and crossed-product algebras. The complexity reduction algorithms for the STBCs constructed are explored using tree based search algorithms. Considering an STBC as a vector space over the set of weight matrices, the problem of characterizing the sphere decoding complexity is addressed using quadratic form representations. The main results are as follows. A sub-class of fast decodable STBCs known as Block Orthogonal STBCs (BOSTBCs) are explored. A set of sufficient conditions to obtain BOSTBCs are explained. How the block orthogonal structure of these codes can be exploited to reduce the SD complexity of the STBC is then explained using a depth first tree search algorithm. Bounds on the SD complexity reduction and its relationship with the block orthogonal structure are then addressed. A set of constructions to obtain BOSTBCs are presented next using Clifford unitary weight designs (CUWDs), Coordinate-interleaved orthogonal designs (CIODs), cyclic division algebras and crossed product algebras which show that a lot of codes existing in literature exhibit the block orthogonal property. Next, the dependency of the ordering of information symbols on the SD complexity is discussed following which a quadratic form representation known as the Hurwitz-Radon quadratic form (HRQF) of an STBC is presented which is solely dependent on the weight matrices of the STBC and their ordering. It is then shown that the SD complexity is only a function of the weight matrices defining the code and their ordering, and not of the channel realization (even though the equivalent channel when SD is used depends on the channel realization). It is also shown that the SD complexity is completely captured into a single matrix obtained from the HRQF. Also, for a given set of weight matrices, an algorithm to obtain a best ordering of them leading to the least SD complexity is presented using the HRQF matrix.