Coordinated multiple point （CoMP） transmission/reception has been investigated recently as a promising technology to increase the cell-edge user performance of long term evolution-advanced （LTE-A）, and channel est...Coordinated multiple point （CoMP） transmission/reception has been investigated recently as a promising technology to increase the cell-edge user performance of long term evolution-advanced （LTE-A）, and channel estimation is a crucial technology for CoMP systems. In this paper, we consider a reduced-complexity minimum mean square error （MMSE） channel estimator for CoMP systems. The estimator uses space alternating generalized expectation maximization （EM） （SAGE） algorithm to avoid the inverse operation of the joint MMSE estimator. In the proposed scheme, the base stations （BSs） in the CoMP system estimate the channels of all the coordinated users serially and iteratively. We derive the SAGE-based estimators and analyze complexity. Simulation results verify that the performance of the proposed algorithm is close to the joint MMSE estimation algorithm while reducing the complexity greatly.展开更多
基金supported by the National Natural Science Foundation of China(60702060)111 Project of China(B08038)+1 种基金the Fundamental Research Funds for the Central Universities (K50510010016)the State Major Projects of the Next Generation Broadband Wireless Mobile Communication Networks (2012ZX03001027-001)
文摘Coordinated multiple point （CoMP） transmission/reception has been investigated recently as a promising technology to increase the cell-edge user performance of long term evolution-advanced （LTE-A）, and channel estimation is a crucial technology for CoMP systems. In this paper, we consider a reduced-complexity minimum mean square error （MMSE） channel estimator for CoMP systems. The estimator uses space alternating generalized expectation maximization （EM） （SAGE） algorithm to avoid the inverse operation of the joint MMSE estimator. In the proposed scheme, the base stations （BSs） in the CoMP system estimate the channels of all the coordinated users serially and iteratively. We derive the SAGE-based estimators and analyze complexity. Simulation results verify that the performance of the proposed algorithm is close to the joint MMSE estimation algorithm while reducing the complexity greatly.
