Iterative reduced-state decoding for coded partial-response channels

The conventional iterative decoding based on the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm rises exponentially in terms of channel memory length. In this paper, we propose a low-complexity soft-input/soft-output (SISO) channel detector based on tentative hard estimates fed back from the outer decoder in the previous iteration. The computational complexity of the proposed detector is polynomial in terms of the channel memory length. To demonstrate the performance/complexity tradeoff of the proposed detector, we present simulation results for 9-tap, 11-tap, and 12-tap channels. We show that the proposed detector significantly reduces the computational complexity with only slight performance degradation compared to the full-complexity BCJR algorithm.