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Báo cáo hóa học: " Research Article Multimode Transmission in Network MIMO Downlink with Incomplete CSI"

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 Multimode Transmission in Network MIMO Downlink with Incomplete CSI | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 743916 13 pages doi 10.1155 2011 743916 Research Article Multimode Transmission in Network MIMO Downlink with Incomplete CSI Nima Seifi 1 Mats Viberg EURASIP Member 1 Robert W. Heath Jr. 2 Jun Zhang 3 and Mikael Coldrey4 1 Department of Signals and Systems Chalmers University of Technology 412 96 Gothenburg Sweden 2 Wireless Networking and Communications Group WNCG Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712-0240 USA 3 Deptartment of Electronic and Computer Engineering Hong Kong University of Science and Technology HKUST Clear Water Bay Kowloon Hong Kong 4Ericsson Research Ericsson AB 417 56 Gothenburg Sweden Correspondence should be addressed to Nima Seifi nima.seifi@chalmers.se Received 2 June 2010 Accepted 16 October 2010 Academic Editor Francesco Verde Copyright 2011 Nima Seifi et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. We consider a cooperative multicell MIMO a.k.a network MIMO downlink system with multiantenna base stations BSs which are connected to a central unit and communicate with multiantenna users. In such a network obtaining perfect channel state information CSI of all users at the central unit to exploit opportunistic scheduling requires a substantial amount of feedback and backhaul signaling. We propose a scheduling algorithm based only on the knowledge of the average SNR at each user from all the cooperating BSs denoted as incomplete CSI. Multimode transmission is applied that is able to adaptively adjust the number of data streams transmitted to each user. Utilizing the results of random matrix theory an analytical framework is proposed to approximate the ergodic rate of each user with different number of data streams.