Radix-Tree Based Spectrum Allocation Model for Cognitive Radio Networks:Maximizing Network Capacity
Cognitive radio(CR)technology is a promising technology that provides opportunistic access to free channels for secondary uers (SUs),and enhances the spectrum effciency 1.In this paper,we present a novel capacity-aware spectrum allocation model for cognitive radio networks.We first modeled interference constraints based on the interference temperature concept and let the SUs to increase their transmission power until the interference temperature on one of their neighbors exceeds its interference temperature threshold.Then,knowing the potential links SINR and bandwidth,we calculated links capacity based on Shannon formula and modeled the co-channel interference between potential lingks on each channel using an interference graph.Finally,we formulated a spectrum assignement problem in the form of a binary integer linear problem(BILP)to find an optimal feasible set of simultaneously active links among all the potential links in an interfernce graph in a way that overall network capacity would be maximized.To reduce complexity,we also proposed a new radix tree based algorithm that,by removing the sparse areas in search space,leads to a considerablem as compared to BILP algorithm.Simulation results have shown that this proposed model leads to a considerable improvement in overall network capacity as compared to genetic algorithm.We also showed that maximizing the number of active lingks between SUs as an objective function does not necessarily maximize the network capacity.
cognitive radio spectrum allocation network capacity interference constraints
Mohammad Yousefvand Siavash Khorsandi Abbas Mohammadi
High Speed Network Lab,Depetment of Information Technology and Computer Engineering Amirkabir University of Techran,Iran
国际会议
2012 IEEE 14th International Conference on Communication Technology(2012年第十四届通信技术国际会议(ICCT 2012))
成都
英文
16-21
2012-11-09（万方平台首次上网日期，不代表论文的发表时间）