Esta tesis estudia la distribución de ficheros en redes inalámbricas, analizando diferentes mecanismos que permiten optimizar la transmisión en términos de ancho de banda y calidad de experiencia. Concretamente, la tesis se centra en la transmisión de ficheros en canales multicast. Dicha transmisión resulta adecuada en ciertos entornos y tiene múltiples aplicaciones, algunas de las cuales se presentan en este trabajo. La tesis analiza en profundidad FLUTE (File Delivery over Unidirectional Transport), un protocolo para el envío fiable de ficheros en canales unidireccionales, y presenta algunas propuestas para mejorar la transmisión a través de dicho protocolo. En este sentido, una de las bases de este protocolo es el uso de un mecanismo llamado Tabla de Envío de Ficheros (FDT), que se utiliza para describir los contenidos transmitidos. Este trabajo analiza cómo la transmisión de la FDT afecta al funcionamiento del protocolo FLUTE, y proporciona una metodología para optimizar el envío de contenido mediante FLUTE. Por otro lado, en la transmisión de ficheros por multicast resulta esencial ofrecer un servicio fiable. Entre los distintos mecanismos utilizados por FLUTE para ofrecer fiabilidad, este trabajo analiza principalmente los códigos de corrección AL-FEC (Application Layer ¿ Forward Error Correction), los cuales añaden redundancia a la transmisión para minimizar los efectos de las pérdidas en el canal. Al respecto, esta tesis evalúa los códigos LDPC Staircase y LDPC Triangle, comparando su funcionamiento bajo diferentes condiciones de transmisión. Además, en el caso de tener un canal de retorno, una de las principales contribuciones de esta tesis es la propuesta de códigos LDPC adaptativos para servicios de descarga de ficheros. En esta clase de códigos, el servidor de contenidos cambia dinámicamente la cantidad de protección FEC proporcionada en función de las pérdidas que detectan los usuarios. La evaluación demuestra el buen funcionamiento de estos códigos en distintos entornos. / De Fez Lava, I. (2014). Evaluation of a content download service based on FLUTE and LDPC for improving the Quality of Experience over multicast wireless networks [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37051 / Premios Extraordinarios de tesis doctorales

Multi-antenna wireless communication systems that employ a large number of antennas have recently stirred a lot of research interest. This is mainly due to the possibility of achieving very high spectral efficiency, power efficiency, and link reliability in such large-scale multiple-input multiple-output (MIMO) systems. An emerging architecture for large-scale multiuser MIMO communications is one where each base station (BS) is equipped with a large number of antennas (tens to hundreds of antennas) and the user terminals are equipped with fewer antennas (one to four antennas) each. The backhaul communication between base stations is also carried out using large number of antennas. Because of the high dimensionality of large-scale MIMO signals, the computational complexity of various transceiver operations can be prohibitively large. Therefore, low complexity techniques that scale well for transceiver signal processing in such large-scale MIMO systems are crucial. The transceiver operations of interest include signal encoding at the transmitter, and channel estimation, detection and decoding at the receiver. This thesis focuses on the design and analysis of novel low-complexity transceiver signal processing schemes for large-scale MIMO systems. In this thesis, we consider two types of large-scale MIMO systems, namely, massive MIMO systems and generalized spatial modulation MIMO (GSM-MIMO) systems. In massive MIMO, the mapping of information bits to modulation symbols is done using conventional modulation alphabets (e.g., QAM, PSK). In GSM-MIMO, few of the avail-able transmit antennas are activated in a given channel use, and information bits are conveyed through the indices of these active antennas, in addition to the bits conveyed through conventional modulation symbols. We also propose a novel modulation scheme named as precoder index modulation, where information bits are conveyed through the index of the chosen precoder matrix as well as the modulation symbols transmitted. Massive MIMO: In this part of the thesis, we propose a novel MIMO receiver which exploits channel hardening that occurs in large-scale MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of HH H become much weaker compared to the diagonal terms as the size of the channel gain matrix H increases. We exploit this phenomenon to devise a low-complexity channel estimation scheme and a message passing algorithm for signal detection at the BS receiver in massive MIMO systems. We refer to the proposed receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The key novelties in the proposed CHEMP receiver are: (i) operation on the matched filtered system model, (ii) Gaussian approximation on the off-diagonal terms of the HH H matrix, and (iii) direct estimation of HH H instead of H and use of this estimate of HH H for detection The performance and complexity results show that the proposed CHEMP receiver achieves near-optimal performance in large-scale MIMO systems at complexities less than those of linear receivers like minimum mean squared error (MMSE) receiver. We also present a log-likelihood ratio (LLR) analysis that provides an analytical reasoning for this better performance of the CHEMP receiver. Further, the proposed message passing based detection algorithm enables us to combine it with low density parity check (LDPC) decoder to formulate a joint message passing based detector-decoder. For this joint detector-decoder, we design optimized irregular binary LDPC codes specific to the massive MIMO channel and the proposed receiver through EXIT chart matching. The LDPC codes thus obtained are shown to achieve improved coded bit error rate (BER) performance compared to off-the-shelf irregular LDPC codes. The performance of the CHEMP receiver degrades when the system loading factor (ratio of the number of users to the number of BS antennas) and the modulation alpha-bet size are large. It is of interest to devise receiver algorithms that work well for high system loading factors and modulation alphabet sizes. For this purpose, we propose a low-complexity factor-graph based vector message passing algorithm for signal detection. This algorithm uses a scalar Gaussian approximation of interference on the basic sys-tem model. The performance results show that this algorithm performs well for large modulation alphabets and high loading factors. We combine this detection algorithm with a non-binary LDPC decoder to obtain a joint detector-decoder, where the field size of the non-binary LDPC code is same as the size of the modulation alphabet. For this joint message passing based detector-decoder, we design optimized non-binary irregular LDPC codes tailored to the massive MIMO channel and the proposed detector. GSM-MIMO: In this part of the thesis, we consider GSM-MIMO systems in point-to-point as well as multiuser communication settings. GSM-MIMO has the advantage of requiring only fewer transmit radio frequency (RF) chains than the number of transmit antennas. We analyze the capacity of point-to-point GSM-MIMO, and obtain lower and upper bounds on the GSM-MIMO system capacity. We also derive an upper bound on the BER performance of maximum likelihood detection in GSM-MIMO systems. This bound is shown to be tight at moderate to high signal-to-noise ratios. When the number of transmit and receive antennas are large, the complexity of en-coding and decoding of GSM-MIMO signals can be prohibitively high. To alleviate this problem, we propose a low complexity GSM-MIMO encoding technique that utilizes com-binatorial number system for bits-to-symbol mapping. We also propose a novel layered message passing (LaMP) algorithm for decoding GSM-MIMO signals. Low computational complexity is achieved in the LaMP algorithm by detecting the modulation bits and the antenna index bits in two deferent layers. We then consider large-scale multiuser GSM-MIMO systems, where multiple users employ GSM at their transmitters to communicate with a BS having a large number of receive antennas. For this system, we develop computationally efficient message passing algorithms for signal detection using vector Gaussian approximation of interference. The performance results of these algorithms show that the GSM-MIMO system outperforms the massive MIMO system by several dBs for the same spectral efficiency. Precoder index modulation: It is known that the performance of a communication link can be enhanced by exploiting time diversity without reducing the rate of transmission using pseudo random phase preceding (PRPP). In order to further improve the performance of GSM-MIMO, we apply PRPP technique to GSM-MIMO systems. PRPP provides additional diversity advantage at the receiver and further improves the performance of GSM-MIMO systems. For PRPP-GSM systems, we propose methods to simultaneously precode both the antenna index bits and the modulation symbols using rectangular precoder matrices. Finally, we extend the idea of index modulation to pre-coding and propose a new modulation scheme referred to as precoder index modulation (PIM). In PIM, information bits are conveyed through the index of a prehared PRPP matrix, in addition to the information bits conveyed through the modulation symbols. PIM is shown to increase the achieved spectral efficiency, in addition to providing diver-sity advantages.

Channel coding plays a vital role in telecommunication. Low-Density Parity- Check (LDPC) codes are linear error-correcting codes. According to the 3rd Generation Partnership Project (3GPP) TS 38.212, LDPC is recommended for the Fifth-generation (5G) New Radio (NR) shared channels due to its high throughput, low latency, low decoding complexity and rate compatibility. LDPC encoding chain has been defined in 3GPP TS 38.212, but some details of LDPC encoding chain are still required to be explored in the MATLAB environment. For example, how to deal with the filler bits for encoding and decoding. However, as the reverse process of LDPC encoding, there is no information on LDPC decoding process for 5G NR shared channels in 3GPP TS 38.212. In this thesis project, LDPC encoding and decoding chains were thoughtfully developed with MATLAB programming based on 3GPP TS 38.212. Several LDPC decoding algorithms were implemented and optimized. The performance of LDPC algorithms was evaluated using block error rate (BLER) v.s. signal to noise ratio (SNR) and CPU time. Results show that the double diagonal structure-based encoding method is an efficient LDPC encoding algorithm for 5G NR. Layered Sum Product Algorithm (LSPA) and Layered Min-Sum Algorithm (LMSA) are more efficient than Sum Product Algorithm (SPA) and Min-Sum Algorithm (MSA). Layered Normalized Min-Sum Algorithm (LNMSA) with proper normalization factor and Layered Offset Min-Sum Algorithm (LOMSA) with good offset factor can optimize LMSA. The performance of LNMSA and LOMSA decoding depends more on code rate than transport block. / Kanalkodning spelar en viktig roll i telekommunikation. Paritetskontrollkoder med låg densitet (LDPC) är linjära felkorrigeringskoder. Enligt tredje generationens partnerskapsprojekt (3GPP) TS 38.212, LDPC rekommenderas för den femte generationens (5G) nya radio (NR) delade kanal på grund av dess höga genomströmning, låga latens, låga avkodningskomplexitet och hastighetskompatibilitet. LDPC kodningskedjan har definierats i 3GPP TS 38.212, men vissa detaljer i LDPC kodningskedjan krävs fortfarande för att utforskas i Matlabmiljön. Till exempel hur man hanterar fyllnadsbitar för kodning och avkodning. Men som den omvända processen för LDPC kodning finns det ingen information om LDPC avkodningsprocessen för 5G NR delade kanaler på 3GPP TS 38.212. I detta avhandlingsprojekt utvecklades LDPC-kodning och avkodningskedjor enligt 3GPP TS 38.212. Flera LDPC-avkodningsalgoritmer implementerades och optimerades. Prestandan för LDPC-algoritmer utvärderades med användning av blockfelshalt (BLER) v.s. signal / brusförhållande (SNR) och CPU-tid. Resultaten visar att den dubbla diagonala strukturbaserade kodningsmetoden är en effektiv LDPC kodningsalgoritm för 5G NR. Layered Sum Product Algorithm (LSPA) och Layered Min-Sum Algorithm (LMSA) är effektivare än Sum Product Algorithm (SPA) och Min-Sum Algorithm (MSA). Layered Normalized Min-Sum Algorithm (LNMSA) med rätt normaliseringsfaktor och Layered Offset Min-Sum Algorithm (LOMSA) med bra offsetfaktor kan optimera LMSA. Prestandan för LNMSA- och LOMSA-avkodning beror mer på kodhastighet än transportblock.