Fractionally spaced blind equalization and estimation of FIR channels

The author considers the problem of blind estimation and equalization of digital communication FIR (finite impulse response) channels using fractionally spaced samples. The problem is cast in a mathematical framework of parameter estimation for a vector stationary process with a single input (information sequence) and multiple outputs, by using a time-series representation of a cyclostationary process. The channel parameters are estimated by nonlinear batch optimization of a quadratic cumulant matching criterion involving second and fourth order cumulants of the received data. A new algorithm is proposed for (asymptotically) globally convergent, linear estimation of the FIR channel parameters where the FIR model order is not necessarily known. A simulation example using QAM (quadrature amplitude modulation) signals is presented.<>