SNR Adaptive Limited Constellation Sphere Decoding

Sphere Decoding algorithm has been shown to achieve near Maximum Likelihood (ML) performance with low complexity for MIMO communication systems, but still has higher complexity than other suboptimum detectors. Especially at low SNR, the complexity of sphere decoding algorithm gets much higher. In this paper, sphere decoding algorithms combined with other suboptimum detectors are proposed. Pre-estimated vectors by suboptimum detectors such as MMSE V-BLAST are used to assist sphere decoding algorithm. The number of search points in the tree search lattice area can be restricted, and the complexity can be reduced significantly. The number of limited constellation points can be changed by considering the trade-off between bit-error-rate (BER) performance and complexity. If we adjust the number of limited points according to SNR, we can achieve the BER performance close to that of an optimal sphere decoding algorithm, and lower complexity than the SchnorrEuchner algorithm.