Soft Information Learning of BICM-ID System Based on Deep Learning
Guoquan Li, Yonghai Xu, Yongjun Xu, Zhengwen Huang, Jinzhao Lin · 2021
In this paper, deep learning is combined to learn the bit posterior probability (soft information) of iterative decoding for a bit-interleaved coded modulation with iterative decoding (BICM-ID) system. The deep neural network (DNN) is adopted to learn and replace multiple modules of the receiver, which can jointly deal with multiple problems and improve the efficiency of the whole system. The output of direct learning iteration reduces the computational cost of iteration to a certain extent. Simulation is carried out under Rayleigh channel and multiple modulation modes and results show that the proposed scheme without iteration is better than traditional BICM systems, and very close to traditional BICM-ID systems which needs iteration between demodulation and decoding.