Reduced-Complexity Turbo Equalization for Coded Intersymbol Interference Channels Based on Local Search Algorithms

We consider the intersymbol interference (ISI) channel detection problem from a combinatorial optimization viewpoint and propose a low-complexity soft-output detector based on heuristic search methods. At each iteration, the proposed receiver views the hard estimate of the transmitted sequence fed back from the outer decoder as an initial solution for optimization. Local search algorithms are then used to optimize a properly defined objective function. Finally, the a posteriori probabilities of transmitted bits are produced based on a candidate list that consists of trial solutions searched in the optimization procedure. Simulation results show that the proposed receiver can significantly reduce the computational complexity with only a small performance loss as compared to the full-complexity Bahl-Cocke-Jelinek-Raviv (BCJR) detector.