Pseudo-maximum-likelihood data estimation algorithm and its application over band-limited channels

A pseudo-maximum-likelihood data estimation (PML) algorithm for discrete ch annels with finite memory in additive white Gaussian noise environment is d eveloped. Unlike the traditional methods that utilize the Viterbi algorithm (VA) for data sequence estimation, the PML algorithm offers an alternative solution to the problem. The simplified PML algorithm is introduced to red uce the computational complexity of the PML algorithm for channels with lon g impulse response. The adaptive version of the PML algorithm suitable for time-varying channels such as frequency-selective Rayleigh fading channels is also introduced. Computer simulation results demonstrate the performance of these algorithms and compare them to the VA-based techniques for differ ent types of channels, The performance design criterion for the PML algorit hm is derived in the Appendix.