Made available in DSpace on 2014-06-12T15:50:41Z (GMT). No. of bitstreams: 1 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2008 / A popularização da Internet e a demanda por acesso de alta velocidade levou ao desenvolvimento da Broadband Wireless Access. Apesar do seu grande potencial, a comunicação via rádio impõe alguns desafios. Uma grande limitação é o próprio meio de transmissão devido a efeitos inerentes à propagação de radio como o path loss, frequency selective fading, espalhamento Doppler e multipath delay-spread. Nesse contexto, o OFDM é uma tecnologia promissora por causa de sua tolerância a problemas de perdas e multi-caminho. Devido à combinação de canais independentes, é possível usar diferentes modulações em cada sub-carrier, de acordo com as condições do canal. Esta técnica é conhecida como adaptive modulation and coding. Além disso, em uma arquitetura ponto a multi-ponto, múltiplos usuários podem compartilhar o espectro ao se atribuir diferentes conjuntos de sub-carriers, tirando vantagem do um efeito conhecido como diversidade multi-usuário. Em comparação com outras técnicas de múltiplo acesso, o OFDMA permite um melhor aproveitamento da diversidade multi-usuário com a possibilidade de uma alocação com alta granularidade. Muitas pesquisas têm investigado técnicas adaptativas capazes de melhorar a eficiência espectral em sistemas multi-usuário. Essas técnicas são normalmente formuladas como constraint optimization problems, conhecidos por serem NP-hard. Neste trabalho, adotamos uma abordagem heurística para lidar com esse tipo de problema. O objetivo principal é desenvolver uma estratégia de alocação fazendo uso eficiente dos recursos disponíveis e maximizando a eficiência espectral total. Entretanto, um estratégia que apenas procura maximizar a eficiência espectral pode gerar um problema relacionado à justiça no compartilhamento de recursos. Outrossim, com a popularização das redes sem fio, é esperado que elas sejam capazes de prover uma maior variedade de serviços com diferentes requisites de QoS e largura de banda. Portanto, procuramos desenvolver um algoritmo que permita ao operador da rede definir esses requisitos. De acordo com eles, o algoritmo deve fornecer o maior throughput possível dentro dos limites estabelecidos por essas restrições

Opportunistic selection algorithms have grown in importance as next generation wireless systems strive towards higher data rates and spectral efficiencies. For example, in orthogonal frequency division multiple access(OFDMA), the system bandwidth is divided into many sub channels. For each sub channel, the user with the highest channel gain is opportunistically assigned to it. .Likewise, in a multi-source, multi-destination (MSD) cooperative relay system, a relay node must be assigned for every source-destination (SD) pair. The assignment decisions are based on local channel knowledge and must be fast so as to maximize the time available for data transmission. We develop novel multiple access based splitting-based selection algorithms for OFDMA and MSD systems. These systems are unique in that the same user and relay can be the most suitable one for multiple sub channels and multiple SD pairs, respectively. For OFDMA systems, we propose an algorithm called Split Select that assigns for every sub channel the user with the highest channel gain over it. For MSD systems, we propose a contention-based en masse assignment (CBEA) algorithm that assigns to each SD pair a relay that is capable of aiding it. Both Split Select and CBEA are fast and scale well with the number of nodes. For example, Split Select requires just 2.2 slots, on average, to assign a sub channel to its best user even when there are an asymptotically large number of contending users. Likewise, CBEA often takes far less than one slot, on average, to assign a relay to each SD pair.

Motivated by the increasing demand for higher data rates, coverage, and spectral efficiency, current and next generation wireless systems adapt transmission parameters and even who is being transmitted to, based on the instantaneous channel states. For example, frequency-domain scheduling(FDS) is an instance of adaptation in orthogonal frequency division multiple access(OFDMA) systems in which the base station opportunistically assigns different subcarriers to their most appropriate user. Likewise ,transmit antenna selection(AS) is another form of adaptation in which the transmitter adapts which subset of antennas it transmits with. Cognitive radio(CR), which is a next generation technology, itself is a form of adaptation in which secondary users(SUs) adapt their transmissions to avoid interfering with the licensed primary users(PUs), who own the spectrum. However, adaptation requires channel state information(CSI), which might not be available apriori at the node or nodes that are adapting. Further, the CSI might not be perfect due to noise or feedback delays. This can result in suboptimal adaptation in OFDMA systems or excessive interference at the PUs due to transmissions by the SUs in CR. In this thesis, we focus on adaptation techniques in current and next generation wireless systems and evaluate the impact of CSI –both perfect and imperfect –on it. We first develop a novel model and analysis for characterizing the performance of AS in frequency-selective OFDMA systems. Our model is unique and comprehensive in that it incorporates key LTE features such as imperfect channel estimation based on dense, narrow band demodulation reference signal and coarse, broad band sounding reference signal. It incorporates the frequency-domain scheduler, the hardware constraint that the same antenna must be used to transmit over all the subcarriers that are allocated to a user, and the scheduling constraint that the allocated subcarriers must all be contiguous. Our results show the effectiveness of combined AS and FDS in frequency-selective OFDMA systems even at lower sounding reference signal powers. We then investigate power adaptation in underlay CR, in which the SU can transmit even when the primary is on but under stringent interference constraints. The nature of the interference constraint fundamentally decides how the SU adapts its transmit power. To this end, assuming perfect CSI, we propose optimal transmit power adaptation policies that minimize the symbol error probability of an SU when they are subject to different interference and transmit power constraints. We then study the robustness of these optimal policies to imperfections in CSI. An interesting observation that comes out of our study is that imperfect CSI can not only increase the interference at the PU but can also decrease it, and this depends on the choice of the system parameters, interference, and transmit power constraints. The regimes in which these occur are characterized.