A Fast Proportionate RLS Adaptive Equalization for Underwater Acoustic Communications

Abstract

In this paper, a low-complexity recursive least squares (RLS) type sparse direct adaptive equalizer (DAE) is proposed for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. The underlying proportionate RLS (PRLS) adaptive filter algorithm is motivated by the idea of proportionate updating (PU) originated in the improved proportionate normalized least mean squares (IPNLMS) adaptive filter scheme. To overcome the high complexity of the PRLS that is quadratic in the filter size, a fast implementation is developed in a way similar to the design of the stable fast transversal filter (SFTF) as a low-complexity approximation of the standard RLS adaptive filter algorithm. The resulting fast version of the PRLS is named the proportionate SFTF (PSFTF). The PSFTF is then adopted to update coefficients of a linear equalizer (LE), which was tested by experimental data collected in at-sea UWA communication trials. Experimental results showed the PSFTFDAE achieves faster convergence and better performance than existing SFTF-DAE and RLS-DAE.