Turbo equalizations for sparse channels

Turbo equalization scheme provides nearly optimal performance but when it is employed in sparse multipath channel environments, the equalizer complexity can prohibit its use. In this paper, we develop a parallel trellis n-tap maximum a posteriori (MAP) equalizer which can consider n dominant taps of sparse channels in the trellis with reasonable complexity It is shown that turbo equalizations employing n-tap MAP equalizer can achieve nearly the same asymptotic performance of optimal maximum likelihood (ML) detector assuming perfect intersymbol interference (ISI) Cancellation which is required for n-tap MAP We also propose a tap allocation scheme for time-varying minimum mean squared error (MMSE) equalizer which can significantly reduce complexity and provide good tracking performance in time-varying channels.