An Iterative QRD-M Detection Algorithm for MIMO Communication System

Multiple input multiple output (MIMO) has been considered as a promising technique for its potential to significantly increase the spectral efficiency and system performance. Lots of detection algorithms have been proposed for MIMO systems in the literature. Among them, maximum likelihood detection (MLD) algorithm provides the best bit error rate (BER) performance. However, the complexity of MLD exponentially increases with the constellation size and the transmit antenna number. Therefore, it is impractical. to use a full MLD without reducing its computational complexity, because it would be prohibitively large for implementation. Recently, several detection algorithms for MIMO systems achieving near-MLD performance have been proposed. The use of QR decomposition with an M-algorithm (QRD-M) and sphere decoding (SD) have been proposed to provide a tradeoff between the system performance and complexity in MIMO communications. However, with the exception of some special cases, their complexity still grows exponentially with increasing dimension of the transmitted signal. Moreover, the complexity of SD has big variations at different SNR values, which results in impractical to use in hardware implementation. To reduce these problems, a new detection scheme, named as iterative QRD-M (IQRD-M), is proposed in the paper. After performing QR decomposition of the channel matrix, the exhaustive search of the last layer is done, the accumulated metrics axe calculated and sorted, which gives an ordered set of the last layer, then QRD-M algorithm axe used to search the left layers with novel termination methods. The proposed algorithm provides the more near-ML performance and with low complexity.