Interference Cancelation in Coherent CDMA Systems Using Parallel Iterative Algorithms

TL;DR

This paper introduces a parallel LMS-PPIC algorithm for interference cancellation in coherent CDMA systems, improving performance by using multiple NLMS algorithms with different step-sizes to stabilize weight magnitudes.

Contribution

It proposes a novel parallel LMS-PPIC method that enhances interference cancellation by adaptively matching weight magnitudes to unity using multiple NLMS algorithms.

Findings

Improved cancellation performance in balanced channels

Effective in unbalanced and time-varying channels

Reduces error propagation across stages

Abstract

Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference cancelation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancelation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of error from one stage to the next one. When all user channels are balanced, the unit magnitude is the principal property of the cancelation weight elements. Based on this fact and using a set of NLMS algorithms with different step-sizes, the parallel LMS-PPIC (PLMS-PPIC) method is proposed. In each iteration of the algorithm, the parameter estimate of the NLMS algorithm is chosen to match the elements' magnitudes of the cancelation weight estimate with unity. Simulation results are given to compare the performance of our method with the LMS-PPIC algorithm in three cases: balanced channel, unbalanced channel and time varying channel.