Multi-user Detection Based on the ECM Iterative Algorithm in Gaussian Noise

摘要

Generally, it is easier to compute the derivation and maximization of the full-likelihood expectation than the calculations of incompletely data maximizing likelihood function. In some cases, even if it is easy to find the full-likelihood expectation, it is difficult to achieve the maximization of the full-likelihood expectation. So a novel approach for multi-user detection based on the ECM iterative algorithm is proposed. Compared with the EM algorithm, the ECM algorithm reduces the computational complexity of the M-step. The results show that the proposed algorithm has well performance and Convergence in Gaussian noise.