Stochastic Belief Propagation-Based Iterative Detection and Decoding for MIMO Systems
Muhao Li, Houren Ji, Xiaosi Tan, Chuan Zhang · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2025
In this brief, a stochastic belief propagation (BP)-based iterative detection and decoding (IDD) for multiple-input and multiple-output (MIMO) system is proposed. We modify the algorithm of BP detection to make it more suitable for stochastic computation and enable the soft message to be transmitted between the detector and decoder in the format of stochastic sequences. Through IDD, the required number of iterations and quantization precision for the detector will decrease. By sharing the stochastic number generator, the hardware complexity of both the detector and decoder can be reduced. Hardware architectural optimizations and the corresponding implementation are also given, and we can implement 64 × 32, four-QAM MIMO system with (128, 64) polar codes with 1.283mm2area consumption. Compared with other detector, the hardware efficiency can be improved by 7.8 times.