Estimation of co-channel signals with linear complexity

To increase wireless system capacity using co-channel signals and multiple receiver antennas, we develop the partitioned Viterbi algorithm (PVA). The PVA estimation complexity increases linearly with each additional co-channe l signal rather than exponentially as it does with joint maximum-likelihood sequence estimation (MLSE). The estimation problem involves multiple signa ls simultaneously transmitted and observed through slow-fading, frequency-s elective channels. Although transmission is assumed to be in bursts accordi ng to a time-division multiple-access scheme, more than one signal can occu py the same time and frequency slot (these signals are referred to as "co-c hannel" signals). Separation and estimation of the symbol bursts is accompl ished by exploiting channel differences. PVA estimation consists of a set o f Viterbi detectors, one per signal, that operate in parallel with cross-co upling to allow approximate interference cancellation by means of tentative decisions. The forward filter of a decision feedback equalizer (DFE) is us ed to "prefilter" received signals prior to PVA estimation. Prefiltering de lays the energy of interfering signals so that tentative decisions become r eliable enough to use. Simulation results show PVA performance remains near -optimal with respect to the performance of joint MLSE.