An ML Decoding Algorithm with Reduced Complexity for Multi-Input Multi-Output Systems

In this paper, employing the 'breadth-first' search algorithm for the decoding of received signals in multi-input multi-output systems, we propose a novel decoder exhibiting the maximum likelihood performance with reduced complexity. The proposed algorithm is compared with the sphere decoder. Simulation results show that the proposed decoder allows significantly lower computational complexity than the sphere decoder.