Iterative (turbo) soft interference cancellation and decoding for coded CDMA

TLDR

Multiple-access and intersymbol interference severely limit reliable communication in multipath CDMA systems, and conventional sliding-window SISO detectors are computationally prohibitive. This paper proposes an iterative receiver structure for decoding multiuser data in a convolutionally coded asynchronous multipath DS‑CDMA system. The receiver iteratively exchanges extrinsic information between a low‑complexity SISO multiuser detector—based on soft interference cancellation and instantaneous LMMSE filtering—and a bank of single‑user SISO channel decoders, using a recursive implementation to reduce complexity. Simulations show that the low‑complexity iterative receiver yields substantial performance gains over the noniterative baseline, and at high SNR it almost completely mitigates MAI and ISI, approaching single‑user performance.

Abstract

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached.