Improved Sphere Decoding Detection Algorithm Based on Lattice-Reduction-Aided

In the massive MIMO system, when the number of users is comparableto the number of base station (BS) antennas, the performance of the linear detection algorithm is not ideal. We start with nonlinear detection and propose a greedy sphere decoding algorithm based on lattice reduction. Lenstra-Lenstra-Lovasz algorithm assists QR decomposition to obtain orthogonal bases and combines the improved sphere decoding algorithm with the greedy strategy. The search tree nodes are reduced more efficiently by searching the smallest PED as the root node. Simulation results show that the proposed algorithm has the characteristics of low complexity and fast convergence. Compared with linear algorithms, the proposed algorithm has a 3-10 [dB] performance improvement when the system bit error rate is 10(-4). Moreover, the algorithm reduces the complexity of the recently proposed K-Best algorithm to a certain extent, and has high engineering application value.