Per-Survivor Processing (PSP)

The principle of Per-Survivor Processing (PSP) provides a general framework for the approximation of likelihood-based data detection (search) algorithms whenever the presence of unknown quantities prevents the precise use of the classical Viterbi Algorithm (VA). The PSP concept is based on the realization that decision-directed estimation of the relevant unknown parameters should be embedded into the structure of the search algorithm itself, thus joining together the two main functions of the receiver. We argue that PSP not only offers superior and robust performance versus the classical segregated-task architectures in many challenging environments, but that it is also the natural way of approaching the decoding problem from first principles, thus making it the appropriate vehicle for integrated-task receiver design. keywords: Per-Survivor Processing, Maximum Likelihood Sequence Detection, Parameter Estimation, Viterbi Algorithm, Adaptive Processing.