Improved depth-first QRD-M detection algorithm for MIMO systems

Maximum Likelihood (ML) detection algorithm has the optimal Bit Error Rate (BER) performance and the highest calculating complexity in Multiple-Input Multiple-Output (MIMO) system especially with high numbers of transmit antenna and modulation order. QR decomposition with M-algorithm (QRD-M) has been proofed to provide near ML detection performance. QRD-M algorithm reduces the complexity by selecting M candidates with the smallest accumulated metrics at each level of the tree search. To achieve near-ML detection performance, M should be set as large as the constellation size which results the increasing of calculating complexity. If reducing candidate branch, the detection performance will become worse. An improved detection scheme, depth-first QRD-M detection algorithm, is presented here. By jointing depth-first search method with QRD-M, the proposed algorithm can provide better tradeoff options by selecting parameters at different values and simulation results show the validity of proposed algorithm. © 2013 Asian Network for Scientific Information.