For cooperative relay multicast networks, the general cross-layer optimization approaches converge to the global optimal value slowly because of the large quantity of relay terminals. However, the mobility of relay te...For cooperative relay multicast networks, the general cross-layer optimization approaches converge to the global optimal value slowly because of the large quantity of relay terminals. However, the mobility of relay terminals requires quick converging optimization strategies to refresh the relay links frequently. Based on the capacity analysis of multiple relay channels, an improved cross-layer optimization scheme is proposed to resolve this problem, in which the bound of the relay selecting region is determined as a pre-processing. Utilizing the primal-dual algorithm, a cross-layer framework with pre-processing optimizes both the relay terminal selection and power allocation with quick convergence. The simulation results prove the effectiveness of the proposed algorithm.展开更多
基金supported by the National Natural Science Foundation of China (60832009)Natural Science Foundation of Beijing (4102044)+1 种基金Innovative Project for Young Researchers in Central Higher Education Institutions (2009RC0119)the New Generation of Broadband Wireless Mobile Communication Networks of Major Projects of National Science and Technology(2009ZX03003-003-01)
文摘For cooperative relay multicast networks, the general cross-layer optimization approaches converge to the global optimal value slowly because of the large quantity of relay terminals. However, the mobility of relay terminals requires quick converging optimization strategies to refresh the relay links frequently. Based on the capacity analysis of multiple relay channels, an improved cross-layer optimization scheme is proposed to resolve this problem, in which the bound of the relay selecting region is determined as a pre-processing. Utilizing the primal-dual algorithm, a cross-layer framework with pre-processing optimizes both the relay terminal selection and power allocation with quick convergence. The simulation results prove the effectiveness of the proposed algorithm.