A Polynomial Complexity Algorithm for Near-optimal Signal Detection in Linear Gaussian Vector Channels

摘要

A near-optimal signal detection algorithm with complexity of O(K log K) is proposed Tor K -input, K -output linear Gaussian vector channels. The proposed algorithm is based on the searching for a monotone sequence with maximum likelihood, under the ranking of sufficient statistics. It is proved that the algorithm can reach the optimal detection result in the case that all cross-correlation values in the linear Gaussian vector channel are identical. Also some simulation results are provided for the case that the cross-correlation values are different. The simulation results show that the performance of the proposed algorithm degrades with the divergence of the cross-correlation values in the linear vector channels. Finally, a method of modifying the correlation matrix is suggested by an example. In this method, a transformation is derived for reducing the divergence of the cross-correlation values of the correlation matrix. A simulation result shows that the proposed algorithm is enhanced further with the transformation.