The Super-Exponential Algorithm of Blind Equalization for Time-Varying Channel Based on Basis Expansion Model

Abstract

Existing algorithms of blind equalization for time-varying channels are slow in convergence, easily interfered, and hard to pinpoint the location of pulsation in the frequency domain. In this paper we present a new blind equalization method that addresses the aforementioned issues. The new solution combines super-exponential algorithm with carrier frequency-offset estimation for time-varying channels. The time-varying channel taps described by the complex exponential basis expansion model (CE-BEM) are expressed as a superposition of time-varying complex exponential bases with time-invariant coefficients. We first employ a super-exponential algorithm to remove the inter-symbol interference caused by time-invariant coefficients. Then we estimate channel pulsation from equalized signals with a carrier frequency-offset estimation algorithm. Compared with existing ones, our solution converges faster with lower inter-symbol interference and easier specification of the pulsation in frequency domain. Simulation results prove the efficiency of the proposed algorithm.