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

SGD Frequency-Domain Space-Frequency Semiblind Multiuser Receiver with an Adaptive Optimal Mixing Parameter

A novel stochastic gradient descent frequency-domain (FD) space-frequency (SF) semiblind multiuser receiver with an adaptive optimal mixing parameter is proposed to improve performance of FD semiblind multiuser receivers with a fixed mixing parameters and reduces computational complexity of suboptimal FD semiblind multiuser receivers in SFBC downlink MIMO MC-CDMA systems where various numbers of users exist. The receiver exploits an adaptive mixing parameter to mix information ratio between the training-based mode and the blind-based mode. Analytical results prove that the optimal mixing parameter value relies on power and number of active loaded users existing in the system. Computer simulation results show that when the mixing parameter is adapted closely to the optimal mixing parameter value, the performance of the receiver outperforms existing FD SF adaptive step-size (AS) LMS semiblind based with a fixed mixing parameter and conventional FD SF AS-LMS training-based multiuser receivers in the MSE, SER and signal to interference plus noise ratio in both static and dynamic environments

Nonlinear Channel Estimation for OFDM System by Complex LS-SVM under High Mobility Conditions

A nonlinear channel estimator using complex Least Square Support Vector Machines (LS-SVM) is proposed for pilot-aided OFDM system and applied to Long Term Evolution (LTE) downlink under high mobility conditions. The estimation algorithm makes use of the reference signals to estimate the total frequency response of the highly selective multipath channel in the presence of non-Gaussian impulse noise interfering with pilot signals. Thus, the algorithm maps trained data into a high dimensional feature space and uses the structural risk minimization (SRM) principle to carry out the regression estimation for the frequency response function of the highly selective channel. The simulations show the effectiveness of the proposed method which has good performance and high precision to track the variations of the fading channels compared to the conventional LS method and it is robust at high speed mobility.Comment: 11 page

Multiuser Detection with Decision-Feedback Detectors and PIC in MC-CDMA System

In this paper we propose an iterative parallel decision feedback (P-DF) receivers associated with parallel interference cancellation (PIC) for multicarrier code division multiple access (MC-CDMA) systems in a Rayleigh fading channel (cost 207). First the most widely detection techniques, minimum mean-squared error MMSE, Maximum Likelihood ML and PIC were investigated in order to compare their performances in terms of Bit Error Rate (BER) with parallel feedback detection P-DFD. A MMSE DF detector that employs parallel decision-feedback (MMSE-P-DFD) is considered and shows almost the same BER performance with MMSE and ML, which present a better result than the other techniques. In a second time, an iterative proposed method based on the multi-stage techniques P-DFD (parallel DFD with two stages) and PIC was exploited to improve the performance of the system