Blind equalization and estimation of FIR communications channels using fractional sampling

Abstract

We consider the problem of blind estimation and equalization of digital communication finite impulse response (FIR) channels using fractionally spaced samples. Fractionally sampled data are cyclostationary rather than stationary. The problem is cast into a mathematical framework of parameter estimation for a vector stationary process with single input (information sequence) and multiple outputs, by using a time-series representation of a cyclostationary process. The channel parameters are estimated by first estimating various subchannels using the second- and the fourth-order cumulant function of the received data, and then appropriately aligning and scaling them. The estimated channel impulse response is then used to construct a linear equalizer. Two illustrative simulation examples using four- and 16-QAM signals are presented where effect of symbol-timing-phase offset is studied via simulations.