tailieunhanh - Báo cáo hóa học: "Research Article Joint Power Allocation for Multicast Systems with Physical-Layer Network Coding"

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 Joint Power Allocation for Multicast Systems with Physical-Layer Network Coding | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2010 Article ID 423234 9 pages doi 2010 423234 Research Article Joint Power Allocation for Multicast Systems with Physical-Layer Network Coding Chunguo Li 1 2 Shiwen He 1 2 Luxi Yang 1 2 and Wei-Ping Zhu3 1 Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University Nanjing 210096 China 2 School of Information Science and Engineering Southeast University Nanjing 210096 China 3 Department of Electrical and Computer Engineering Concordia University Montreal QC Canada H3G 1M8 Correspondence should be addressed to Luxi Yang Received 31 December 2009 Accepted 7 June 2010 Academic Editor Wen Chen Copyright 2010 Chunguo Li 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. This paper addresses the joint power allocation issue in physical-layer network coding PLNC of multicast systems with two sources and two destinations communicating via a large number of distributed relays. By maximizing the achievable system rate a constrained optimization problem is first formulated to jointly allocate powers for the source and relay terminals. Due to the nonconvex nature of the cost function an iterative algorithm with guaranteed convergence is developed to solve the joint power allocation problem. As an alternative an upper bound of the achievable rate is also derived to modify the original cost function in order to obtain a convex optimization solution. This approximation is shown to be asymptotically optimal in the sense of maximizing the achievable rate. It is confirmed through Monte Carlo simulations that the proposed joint power allocation schemes are superior to the existing schemes in terms of achievable rate and cumulative distribution function .