A soft-output parallel stack algorithm for MIMO detection

In this paper, we propose a parallel stack algorithm for MIMO detection to reduce memory and achieve high throughput. Through partitioning the global stack into multiple local stacks and assigning them to each non-leaf layer of the tree, the proposed algorithm performs the best-first strategy on all stacks in parallel. The parallel processing reduces the iteration loops per detection, and the node pruning rule and the leaf enumeration method help decrease the total stack size. Moreover, a Dual-term APP approach is designed for the proposed algorithm to improve BER performance without extra iteration loops. The simulation results demonstrate that the proposed algorithm reduces the minimum required stack size and the average number of iteration loops per detection of advanced stack algorithm by 50% and 30% respectively to achieve the same BER performance with STS-SD for a 4×4 64QAM MIMO system.