Low complexity MIMO detection algorithm by combining modified OSIC and ML detection

Abstract

The Ordered Successive Interference Cancellation (OSIC) algorithm has the advantage of high capabilities. Moreover, as compared to Maximum Likelihood Detection it has poor performance but its error rate is expected. The OSIC algorithm complexity is based on matrix inversion. In this paper, an improved OSIC algorithm is proposed, that uses a parallel detection and an accurate detection value of combining programs while maintaining performance with the slight reduced computational complexity. Considering the error propagation of the traditional OSIC algorithm, modified OSIC and ML detection algorithm are merged, the use of exhaustive search ML method is to improve the overall performance. In order to avoid the computational complexity of ML algorithm, “k” symbols are selected to be detected by the modified OSIC. The remaining symbols are detected by ML detection. The simulations are performed in MATLAB and it shows that the performance of the proposed algorithm is better than the conventional OSIC algorithm.