To solve the problem of symbol detection in the intersymbol interference (ISI) channel of spatial diversity systems,an iterative blind equalization algorithm was proposed for single-input multiple-ouput (SIMO) communication systems based on the Gibbs sampler method.The conditional posterior distributions of all unknown quantities such as channel impulse response,transmitted symbol sequence were derived in SIMO systems.The unknown quantities were updated one by one from such conditional distributions,so that the maximum a posteriori (MAP) estimates of these unknowns were accomplished in an iterative manner.A salient feature of the equalization algorithm was that it had a soft-input soft-output (SISO) structure.Hence,it was well suited for iterative processing in a coded communication system,which allowed the blind equalization to improve its performance.Simulation results showed that the iterative blind equalization algorithm performs closely to the algorithm with channel response perfectly known to the receiver in severe ISI channels.Performance gap between this approach and channels with no ISI is only 1 dB.
