New channel estimation and multiuser detection algorithms for multicarrier(MC)-CDMA communications systems

Abstract

Multicarrier code division multiple access (MC-CDMA) has been recently proposed as an efficient multicarrier transmission scheme for supporting multiple access communications. However, MC-CDMA is an interference-limited system, which is rather sensitive to multiple access interference (MAI). Multiuser detection techniques are critical to mitigate MAI. Meanwhile, channel estimation is essential to the coherent detection of MC-CDMA signals. This thesis explores to new channel estimation and multiuser detection algorithms for wireless MC-CDMA systems. New blind constrained minimum output energy (CMOE)-based and subspace-based multiuser detection and channel estimation algorithms are first developed. In particular, a new blind CMOE receiver is proposed. The proposed CMOE receiver is based on recursive least square (RLS) updating, and it minimizes the receiver's output energy while preserving the components of the desired signal. By imposing quadratic weight constraint, the CMOE detector is made more robust against the channel and correlation matrix estimation errors, and a better performance over the standard CMOE detector is obtained. The steady-state signal-to-interference-plus-noise ratio (SINR) performance of the blind adaptive CMOE and training adaptive minimum mean squared-error (MMSE) detectors is also analyzed. A blind mode decision-directed MMSE detector is then proposed to further improve the performance of the blind CMOE receivers. Simulation results show that the blind mode decision-directed MMSE detector substantially improves the system performance when the frequency-selective channel is slowly varying. Blind and group-blind subspace-based MMSE multiuser detectors are also developed, where the channel coefficients can be blindly estimated. The proposed group-blind multiuser detector considerably outperforms the blind subspace-based method in uplink MC-CDMA channels. It exploits the spreading codes of a group of known users within the cell, while suppressing the unknown interferers from other cells using the MMSE principle. The adaptive implementation of the blind and group-blind multiuser detectors is also studied, based on signal and noise subspace tracking algorithms. (Abstract shortened by UMI.)