Sphere decoding algorithm for multiuser detection in a distributed antenna system

Abstract

Abstract:In this paper, the impact of initial search radius on the complexity and performance of a sphere decoding algorithm is investigated for different user positions within a distributed antenna system. In a distributed antenna system, users can take up random positions within the cell clusters. The channel matrix can therefore take up infinitely different forms. In the presented work, a distributed antenna system with three different user positions in the cooperating cells is considered by employing different channel matrices. The effect on the complexity and performance of the sphere decoder due to the choice of the initial sphere radius is investigated for these user positions. It is shown that the signal lattice volume changes considerably for different user positions within the cells. A dynamic radius allocation algorithm is proposed in which the behavior is exploited by dynamically adjusting the initial sphere radius based on the knowledge of the channel path gain matrix. The simulation results show that the proposed algorithm results in a considerable reduction in the complexity of the sphere decoder in a distributed antenna system. Additionally, the performance of the sphere decoder in different coupling scenarios within the distributed antenna system has been investigated for a different number of candidates. It is shown that the performance of cell edge users can be considerably enhanced with high channel diversity, which otherwise could severely deteriorate the overall system performance.

Soft-Output Deep-LAS Detection for Coded MIMO System: A Learning-Aided LLR Approximation

“…Subsequently, the best counter estimate x′ for ith bit in nth symbol is searched with in the search space S limited to M Nt /2 symbols on the M-QAM constellation grid. This new search space contains only the counter symbols, and the best solution from all neighbors in S is selected based on (8). Like in step 1, all the possible neighbor vectors are searched iteratively conditioned that the cost difference in the two consecutive search iterations is not positive.…”

“…The soft-output SD algorithm for MIMO and distributed antenna systems was proposed in [8], [9], where the authors showed that for the worst-case scenario the SD's performance could be improved by precise and low-complexity estimation of soft-output for SD. Nevertheless, the detection complexity of SD is still higher in high dimensional MIMO systems.…”