Abstract

Multiuser demodulation algorithms for centralized receivers of asynchronous direct-sequence (DS) spread-spectrum code-division multiple-access (CDMA) systems in frequency-selective fading channels are studied. Both DS-CDMA systems with short (one symbol interval) and long (several symbol intervals) spreading sequences are considered.

Linear multiuser receivers process ideally the complete received data block. The approximation of ideal infinite memory-length (IIR) linear multiuser detectors by finite memory-length (FIR) detectors is studied. It is shown that the FIR detectors can be made near-far resistant under a given ratio between maximum and minimum received power of users by selecting an appropriate memory-length. Numerical examples demonstrate the fact that moderate memory-lengths of the FIR detectors are sufficient to achieve the performance of the ideal IIR detectors even under severe near-far conditions.

Multiuser demodulation in relatively fast fading channels is analyzed. The optimal maximum likelihood sequence detection receiver and suboptimal receivers are considered. The parallel interference cancellation (PIC) receiver is demonstrated to achieve better performance in known channels than the decorrelating receiver, but it is observed to be more sensitive to channel coefficient estimation errors than the decorrelator. At high channel loads the PIC receiver suffers from bit error rate (BER) saturation, whereas the decorrelating receiver does not. Choice of channel estimation filters is shown to be crucial if low BER is required. Data-aided channel estimation is shown to be more robust than decision-directed channel estimation, which may suffer from BER saturation caused by hang-ups at high signal-to-noise ratios.

Multiuser receivers for dynamic CDMA systems are studied. Algorithms for ideal linear detector computation are derived and their complexity is analyzed. The complexity of the linear detector computation is a cubic function of KL, where K and L are the number of users and multipath components, respectively. Iterative steepest descent, conjugate gradient, and preconditioned conjugate gradient algorithms are proposed to reduce the complexity. The computational requirements for one iteration are a quadratic function of KL. The iterative detectors are also shown to be applicable for parallel implementation. Simulation results demonstrate that a moderate number of iterations yields the performance of the corresponding ideal linear detectors. A quantitative analysis shows that the PIC receivers are significantly simpler to implement than the linear receivers and only moderately more complex than the conventional matched filter bank receiver.