A Reliable and Computationally Efficient Soft-Output Fixed-Complexity Sphere Decoder for Large-Scale MIMO Systems

This paper explores a robust and computationally efficient soft-output fixed-complexity sphere decoder (FSD) designed for large-scale multiple-input multiple-output (MIMO) detection. A partial expansion strategy is designed for the first two layers of the proposed FSD, utilizing enumeration orders for both the real and imaginary components of the signal space. Additionally, a section-wise list candidate selection method, incorporating an innovative grouping strategy, is specifically designed for the leaf layer. These techniques complement each other to significantly reduce computational complexity and minimize processing delays. Furthermore, log-likelihood ratio (LLR) refinement is implemented to counteract overestimation caused by the bit-flipping algorithm, leading to notable improvements in error performance. Simulation results demonstrate that the proposed soft-output FSD achieves superior error performance compared to benchmark schemes and approaches the list sphere decoder, while maintaining significantly lower complexity.