A reduced-complexity sphere decoding algorithm for MIMO systems

Sphere decoding (SD), as an algorithm searching for the closest lattice point within a certain search radius, is a corrected maximum likelihood (ML) algorithm for multiple- input multiple-output (MIMO) systems, with low complexity. The sphere radius and the number of search floating points visited throughout the tree traversal searching are the decisive factors for the complexity of the algorithm. In this paper, a new reduce-complexity detection algorithm based on the complex SD for MIMO systems is presented. The algorithm performs a fixed number of total search floating points to detect the p-QAM modulation symbols independently on the noise level. Simulation results show that with 4×4 system via 4-QAM and 16-QAM, the new SD algorithm has a lower complexity than the conventional SD at low signal-noise ratio (SNR) especially.