A Recursive QR Approach to Adaptive Equalization of Time-Varying MIMO Channels

Abstract

This paper presents a novel adaptive equalization algorithm for time-varying MIMO systems with ISI channel conditions. The algorithm avoids channel estimation before equalization and leads to a direct QR-based procedure for updating the equalizer coefficients to track the time-varying channel characteristics. Our approach does not require precise channel estimation and needs relatively few pilot symbols for satisfactory equalization. The theoretical foundations of the proposed algorithm are rooted in signal recovery results derived from the generalized Bezout identity and the finite alphabet property inherent in digital communication schemes. Concerning the convergence behavior of the algorithm, we address the following three issues: existence of fixed points, exclusiveness of fixed points, and robustness under noise disturbance and parameter selection. The equalizer demonstrates promising capability in achieving low symbol error rates for a very broad range of SNRs. Simulation results are presented confirming that this approach outperforms the more traditional recursive least squares (RLS) adaptive equalizer for this application and rivals the performance of MMSE equalizers requiring channel knowledge.