Multistep linear predictors-based blind equalization of FIR/IIR single-input multiple-output channels with common zeros

The problem of blind equalization of single-input multiple-output (SIMO) communications channels is considered using only the second order statistics of the data. Such models arise when a single receiver data is fractionally sampled (assuming that there is excess bandwidth) or when an antenna array is used with or without fractional sampling. We extend the multistep linear prediction approach to infinite impulse response (IIR) channels as well as to the case where the “subchannel” transfer functions have common zeros. In the past, this approach has been confined to finite impulse response (FIR) channels with no common subchannel zeros. We focus on the design of finite-length minimum mean-square error (MMSE) blind equalizers. Knowledge of the nature of the underlying model (FIR or IIR) or the model order is not required. Our approach works when the “subchannel” transfer functions have common zeros as long as the common zeros are minimum-phase zeros. Illustrative simulation examples are provided