In traditional cognitive radio (CR) network, most existing graph-based spectrum allocation schemes don't take on-off behavior of primary users (PUs) into consideration. In this paper, a novel spectrum allocation a...In traditional cognitive radio (CR) network, most existing graph-based spectrum allocation schemes don't take on-off behavior of primary users (PUs) into consideration. In this paper, a novel spectrum allocation algorithm based on the activities of the PUs is proposed. The proposed algorithm mainly focuses on the vacant probability of licensed spectrums. And it allocates the vacant spectrums considering the interference to the neighbor cognitive nodes and the probability fairness of different cognitive nodes during the allocation. Based on the definition of the obtained benefit of cognitive node, new utility functions are formulated to characterize the system total spectrum utilization and fairness performance from the perspective of available probability. The simulation results validate that the proposed algorithm with low system communication cost is more effective than the traditional schemes when the available licensed spectrums are not sufficient, which is effective and meaningful to a real CR system with bad network condition.展开更多
基金Sponsored by the National Natural Science Foundation and Civil Aviation Administration of China(Grant No.61071104 and 61101122)Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory(Grant No.ITD-U12004/K1260010)the National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant No.2012ZX03004-003)
文摘In traditional cognitive radio (CR) network, most existing graph-based spectrum allocation schemes don't take on-off behavior of primary users (PUs) into consideration. In this paper, a novel spectrum allocation algorithm based on the activities of the PUs is proposed. The proposed algorithm mainly focuses on the vacant probability of licensed spectrums. And it allocates the vacant spectrums considering the interference to the neighbor cognitive nodes and the probability fairness of different cognitive nodes during the allocation. Based on the definition of the obtained benefit of cognitive node, new utility functions are formulated to characterize the system total spectrum utilization and fairness performance from the perspective of available probability. The simulation results validate that the proposed algorithm with low system communication cost is more effective than the traditional schemes when the available licensed spectrums are not sufficient, which is effective and meaningful to a real CR system with bad network condition.