MIMOPack: A High Performance Computing Library for MIMO Communication Systems

[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 voleRamiro 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/10251/53930TESISPremios Extraordinarios de tesis doctorale

Signal Processing for Compressed Sensing Multiuser Detection

The era of human based communication was longly believed to be the main driver for the development of communication systems. Already nowadays we observe that other types of communication impact the discussions of how future communication system will look like. One emerging technology in this direction is machine to machine (M2M) communication. M2M addresses the communication between autonomous entities without human interaction in mind. A very challenging aspect is the fact that M2M strongly differ from what communication system were designed for. Compared to human based communication, M2M is often characterized by small and sporadic uplink transmissions with limited data-rate constraints. While current communication systems can cope with several 100 transmissions, M2M envisions a massive number of devices that simultaneously communicate to a central base-station. Therefore, future communication systems need to be equipped with novel technologies facilitating the aggregation of massive M2M. The key design challenge lies in the efficient design of medium access technologies that allows for efficient communication with small data packets. Further, novel physical layer aspects have to be considered in order to reliable detect the massive uplink communication. Within this thesis physical layer concepts are introduced for a novel medium access technology tailored to the demands of sporadic M2M. This concept combines advances from the field of sporadic signal processing and communications. The main idea is to exploit the sporadic structure of the M2M traffic to design physical layer algorithms utilizing this side information. This concept considers that the base-station has to jointly detect the activity and the data of the M2M nodes. The whole framework of joint activity and data detection in sporadic M2M is known as Compressed Sensing Multiuser Detection (CS-MUD). This thesis introduces new physical layer concepts for CS-MUD. One important aspect is the question of how the activity detection impacts the data detection. It is shown that activity errors have a fundamentally different impact on the underlying communication system than data errors have. To address this impact, this thesis introduces new algorithms that aim at controlling or even avoiding the activity errors in a system. It is shown that a separate activity and data detection is a possible approach to control activity errors in M2M. This becomes possible by considering the activity detection task in a Bayesian framework based on soft activity information. This concept allows maintaining a constant and predictable activity error rate in a system. Beyond separate activity and data detection, the joint activity and data detection problem is addressed. Here a novel detector based on message passing is introduced. The main driver for this concept is the extrinsic information exchange between different entities being part of a graphical representation of the whole estimation problem. It can be shown that this detector is superior to state-of-the-art concepts for CS-MUD. Besides analyzing the concepts introduced simulatively, this thesis also shows an implementation of CS-MUD on a hardware demonstrator platform using the algorithms developed within this thesis. This implementation validates that the advantages of CS-MUD via over-the-air transmissions and measurements under practical constraints

Extending the user capacity of MU-MIMO systems with low detection complexity and receive diversity

Multiple-input multiple-output (MIMO) based technologies are considered as an integral part of the upcoming 5G communications to fulfil the ever-increasing demands of wireless applications with high spectral efficiency requirements. However, in uplink multiuser MIMO (MU-MIMO) channels, the number of allowed users is limited by the number of receive antennas associated with radio frequency (RF) chains at the base-station and the complexity burden of multiuser detection (MUD). In this paper, a novel group layer MU-MIMO scheme with low complexity MUD is proposed to increase the number of served users well beyond the available RF chains. By taking the advantage of power control and inherent path loss in cellular systems, the allowed users are divided into groups based on their received power. Efficient group power allocation and group layer MUD (GL-MUD) are utilized to provide a valuable tradeoff between complexity and achieved performance. Furthermore, when more receive antennas than RF chains is implemented, a generalized norm based antenna selection algorithm is proposed to enhance the error performance. Symbol error probability expressions are derived and the effectiveness of proposed scheme is demonstrated through numerical simulations compared with the conventional MU-MIMO and non-orthogonal multiple-access (NOMA) systems over Rayleigh fading channels. The results show a substantial increase in user capacity up to two-fold for the available number of RF chains. In addition, significant signal-to-noise ratio gain is achieved using GL-MUD compared with different MUD techniques

Reduced Receivers for Faster-than-Nyquist Signaling and General Linear Channels

Fast and reliable data transmission together with high bandwidth efficiency are important design aspects in a modern digital communication system. Many different approaches exist but in this thesis bandwidth efficiency is obtained by increasing the data transmission rate with the faster-than-Nyquist (FTN) framework while keeping a fixed power spectral density (PSD). In FTN consecutive information carrying symbols can overlap in time and in that way introduce a controlled amount of intentional intersymbol interference (ISI). This technique was introduced already in 1975 by Mazo and has since then been extended in many directions. Since the ISI stemming from practical FTN signaling can be of significant duration, optimum detection with traditional methods is often prohibitively complex, and alternative equalization methods with acceptable complexity-performance tradeoffs are needed. The key objective of this thesis is therefore to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance. Although the performance of a detector can be measured by several means, this thesis is restricted to bit error rate (BER) and mutual information results. FTN signaling is applied in two ways: As a separate uncoded narrowband communication system or in a coded scenario consisting of a convolutional encoder, interleaver and the inner ISI mechanism in serial concatenation. Turbo equalization where soft information in the form of log likelihood ratios (LLRs) is exchanged between the equalizer and the decoder is a commonly used decoding technique for coded FTN signals. The first part of the thesis considers receivers and arising stability problems when working within the white noise constraint. New M-BCJR algorithms for turbo equalization are proposed and compared to reduced-trellis VA and BCJR benchmarks based on an offset label idea. By adding a third low-complexity M-BCJR recursion, LLR quality is improved for practical values of M. M here measures the reduced number of BCJR computations for each data symbol. An improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed. When combined with a delayed and slightly mismatched receiver, the decoding allows a smaller M without significant loss in BER. The second part analyzes the effect of the internal metric calculations on the performance of Forney- and Ungerboeck-based reduced-complexity equalizers of the M-algorithm type for both ISI and multiple-input multiple-output (MIMO) channels. Even though the final output of a full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of observation model does not impact the detection complexity as the underlying algorithm is unaltered. The last part of the thesis is devoted to a different complexity reducing approach. Optimal channel shortening detectors for linear channels are optimized from an information theoretical perspective. The achievable information rates of the shortened models as well as closed form expressions for all components of the optimal detector of the class are derived. The framework used in this thesis is more general than what has been previously used within the area