Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems

Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a “rank-deficient” scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new Genetic Algorithm (GA) assisted iterative Joint Channel Estimation and Multi-User Detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the Forward Error Correction (FEC) or channel decoder, which inevitably limits the system’s achievable performance. By contrast, our proposed GA is capable of providing “soft” outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme. Index Terms—Channel estimation, genetic algorithm, multiple-input-multiple-output, multi-user detection, orthogonal frequency division multiplexing, space division multiple access

Iterative Joint Channel Estimation and Symbol Detection for Multi-User MIMO OFDM

Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM literature, no channel estimation technique allows the number of users to be higher than the number of receiver antennas, which is often referred to as an “overloaded” scenario. In this contribution we propose a new Genetic Algorithm (GA) assisted iterative joint channel estimation and multiuser detection approach for MIMO SDMA-OFDM systems, which exhibits a robust performance in the above-mentioned overloaded scenario. Furthermore, GA-aided Multi-User Detection (MUD) techniques found in the literature can only provide a hard-decision output, while the proposed GA is capable of providing “soft” outputs, hence achieving an improved performance with the aid of channel decoders. Finally, a range of simulation results are provided to demonstrate the superiority of the proposed scheme

Esquemas de pré-codificação IA com IB-DFE para sistemas MC-CDMA

Mestrado em Engenharia Eletrónica e TelecomunicaçõesTo achieve high bit rates, needed to meet the quality of service requirements of future multimedia applications, multi-carrier code division multiple access (MC-CDMA) has been considered as a candidate air-interface. Interference alignment (IA) is a promising technique that allows high capacity gains in interfering channels. On the other hand, iterative block decision feedback equalization (IB-DFE) based receivers can efficiently exploit the inherent space-frequency diversity of the MIMO MC-CDMA systems. In this thesis we proposed an IA precoding at the transmitter with IB-DFE based processing at the receiver for MC-CDMA systems. The IA precoding is applied at chip level instead of the data symbols level, as in the conventional IA based systems. The receiver is designed in two steps: first the equalizers based on zero forcing (ZF) or minimum mean square error (MMSE) are used to remove the aligned users´ interference. Then and after a whitening noise process, an IB-DFE based equalizer is designed to remove both the residual inter-user aligned and inter-carrier interferences. The results have shown that the obtained performance is very close to the one obtained by the optimal matched filter, with few iterations at the receiver side.Para atingir maiores ritmos de transmissão, as futures aplicações multimédia necessitam de atingir a qualidade de serviço necessária. Para isso, o multi-carrier code division multiple access (MC-CDMA) tem sido apontado como um forte candidato para interface ar dos futuros sistemas celulares. O Interference Alignment (IA) ou alinhamento de interferência é uma técnica promissora que permite ter altos ganhos de capacidade em canais com interferência. Por outro lado, temos receptores baseados no conceito iterative block decision feedback equalization(IB-DFE) que conseguem tirar partido, de uma forma eficiente, da inerente diversidade espaço-frequência dos sistemas MIMO MC-CDMA. Nesta dissertação é implementada uma pré-codificação baseada no conceito de IA considerando três transmissores (ou estações base) juntamente, com um processamento IB-DFE no receptor para sistemas MC-CDMA.A pré-codificação é aplicada ao nível de chip em vez de ser aplicado ao nível dos dados. O receptor é projectado em dois passos: em primeiro lugar equalizadores baseados em ZF ou em MMSE são utilizados para remover a interferência alinhada dos restantes utilizadores. De seguida, e após aplicar um processo de branqueamento do ruído ao sinal à saída do primeiro equalizador, um segundo equalizador baseado em IB-DFE é projectado para remover a interferência inter-utilizador residual e também a interferência residual entre portadoras. Os resultados obtidos mostraram-se satisfatórios na remoção da interferência obtendo-se um desempenho muito próximo do obtido considerando um filtro adaptado

Multiple-antenna-aided OFDM employing genetic-algorithm-assisted minimum bit error rate multiuser detection

The family of minimum bit error rate (MBER) multiuser detectors (MUD) is capable of outperforming the classic minimum mean-squared error (MMSE) MUD in terms of the achievable bit-error rate (BER) owing to directly minimizing the BER cost function. In this paper,wewill invoke genetic algorithms (GAs) for finding the optimum weight vectors of the MBER MUD in the context of multiple-antenna-aided multiuser orthogonal frequency division multiplexing (OFDM) .We will also show that the MBER MUD is capable of supporting more users than the number of receiver antennas available, while outperforming the MMSE MUD