Low-Complexity Variable Forgetting Factor Techniques for RLS Algorithms in Interference Rejection Applications

TL;DR

This paper introduces a low-complexity variable forgetting factor mechanism for RLS algorithms that improves interference suppression in DS-CDMA systems by enhancing convergence and tracking with analytical performance predictions.

Contribution

It presents a novel VFF mechanism based on error correlation, providing faster convergence and better tracking with reduced computational complexity.

Findings

Achieves superior interference rejection performance

Provides analytical expressions for mean squared error

Demonstrates effectiveness in nonstationary environments

Abstract

We propose a low-complexity variable forgetting factor (VFF) mechanism for recursive least square (RLS) algorithms in interference suppression applications. The proposed VFF mechanism employs an updated component related to the time average of the error correlation to automatically adjust the forgetting factor in order to ensure fast convergence and good tracking of the interference and the channel. Convergence and tracking analyses are carried out and analytical expressions for predicting the mean squared error of the proposed adaptation technique are obtained. Simulation results for a direct-sequence code-division multiple access (DS-CDMA) system are presented in nonstationary environments and show that the proposed VFF mechanism achieves superior performance to previously reported methods at a reduced complexity.