Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Optimal Power Allocation with Channel Inversion Regularization-Based Precoding for MIMO Broadcast Channels | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 587243 8 pages doi 2008 587243 Research Article Optimal Power Allocation with Channel Inversion Regularization-Based Precoding for MIMO Broadcast Channels Yang Xu and Tho Le-Ngoc Department of Electrical and Computer Engineering Faculty of Engineering McGill University 3480 University Street Montreal QC Canada H3A 2A7 Correspondence should be addressed to Tho Le-Ngoc Received 9 July 2008 Revised 24 October 2008 Accepted 31 December 2008 Recommended by Huaiyu Dai Zero-forcing ZF precoding scheme can achieve the asymptotic sum capacity as dirty-paper coding DPC in multiple-input multiple-output broadcast MIMO-BC channel when the number of users K approaches infinity. However the gap between ZF and DPC is not negligible in a practical range of K that is K 100. The capacity loss is partly due to the excessive transmission power penalty incurred by ZF when the channel matrix of the selected user subset is poorly conditioned. To avoid this power penalty we propose to use a variation of ZF channel inversion regularization CIR as a precoding scheme in MIMO-BC channels. But unlike the interference-free ZF the problem of maximizing sum-rate capacity using CIR precoding becomes nonconvex which cannot be solved by water-filling strategy. Thus we propose an efficient algorithm based on gradient projection GP as the optimal power allocation strategy for selected users and show that the proposed CIR precoding scheme can achieve asymptotically the optimum sum-rate of the DPC strategy. Moreover simulation results show that the CIR precoding scheme with the proposed optimal power allocation scheme achieves better sum-rate performance than ZF for a wide range of K. Copyright 2008 Y. Xu and T. Le-Ngoc. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in
