Low Complexity Joint Iterative Equalization and Multiuser Detection in Dispersive DS-CDMA Channels

TL;DR

This paper introduces a low-complexity joint equalization and multiuser detection algorithm for dispersive DS-CDMA channels, achieving near-optimal performance with reduced computational complexity and higher system load capacity.

Contribution

It develops a reduced state trellis search detection algorithm based on decision feedback, significantly lowering complexity while maintaining near-optimal detection performance.

Findings

Achieves near-optimal performance at moderate SNR

Attains larger system load capacity than parallel interference cancellation

Validated through analysis and simulations in large-system limit

Abstract

Communications in dispersive direct-sequence code-division multiple-access (DS-CDMA) channels suffer from intersymbol and multiple-access interference, which can significantly impair performance. Joint maximum \textit{a posteriori} probability (MAP) equalization and multiuser detection with error control decoding can be used to mitigate this interference and to achieve the optimal bit error rate. Unfortunately, such optimal detection typically requires prohibitive computational complexity. This problem is addressed in this paper through the development of a reduced state trellis search detection algorithm, based on decision feedback from channel decoders. The performance of this algorithm is analyzed in the large-system limit. This analysis and simulations show that this low-complexity algorithm can obtain near-optimal performance under moderate signal-to-noise ratio and attains larger system load capacity than parallel interference cancellation.