Noise can help weak information bearing signal to be detected in nonlinear systems by the use of stochastic perturbation. In this paper, we propose a novel belief propagation list (BPL) decoder that relies on artificial noise. The proposed decoder is constructed by using parallel independent BP decoders. Noise with different powers are added to different BP decoders that runs in parallel, and the output of the decoder that pass the early detection and termination criteria check is considered as the recovered data. Adding small amount of noise enables the decoder to handle un-converged errors. The obtained results show that the performance of Noise-aided BPL decoder is much better than the performances of BP, successive cancelation (SC) and successive cancelation list (SCL) decoders, and it is a bit behind of cyclic redundancy check aided SCL in terms of bit-error rate performance.

Parallel decodable turbo codes (PDTCs) are suitable for concurrent decoding and hence have low latency. Memory collision issue is an important problem met during parallel processing. In this article, we propose a collision free interleaver for parallel processing operations. The performance of PDTCs is analyzed with the proposed random interleaver preventing the memory collision problem. Distance spectra of PDTCs with the proposed interleaver are computed and compared to those with S-random interleaver.