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Comparing RLS and LMS adaptive equalizers for nonstationary wireless channels in mobile ad hoc networks

The paper compares performance of finite impulse response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square (LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation results, in terms of steady-state mean-square estimation error (MSE) and average bit-error rate (BER) metrics, are found for the frequency-selective Rayleigh fading wireless channel experienced in a mobile ad hoc network where nodes are lognormally shadowed from each other. For the nonstationary channel models considered, RLS is always found to outperform LMS.