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.