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Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks
Affiliation:1. School of Computer Science and IT, RMIT University, Victoria, Australia;2. School of Computer Science, University of Oklahoma, Norman, OK 73019-6151, USA;1. Department of Electrical and Computer Engineering, Virginia Tech, United States;2. Department of Computer Science, Virginia Tech, United States;3. Dept. of Bioinformatics and Biomedical Engineering, Asia University, Taiwan;4. Dept. of Information Management, Southern Taiwan University of Science and Technology, Taiwan;1. National ICT for Australia (NICTA), School of Computer Science, RMIT University, Melbourne VIC 3001, Australia;2. University of Oklahoma, School of Computer Science, University of Oklahoma, Norman, OK 73019-6151, United States
Abstract:Cognitive radio and Dynamic Spectrum Access (DSA) enable wireless users to share a wide range of available spectrums. In this paper, we study joint spectrum allocation and scheduling problems in cognitive radio wireless networks with the objectives of achieving fair spectrum sharing. A novel Multi-Channel Contention Graph (MCCG) is proposed to characterize the impact of interference under the protocol model in such networks. Based on the MCCG, we present an optimal algorithm to compute maximum throughput solutions. As simply maximizing throughput may result in a severe bias on resource allocation, we take fairness into consideration by presenting optimal algorithms as well as fast heuristics to compute fair solutions based on a simplified max–min fairness model and the well-known proportional fairness model. Numerical results show that the performance given by our heuristic algorithms is very close to that of the optimal solution, and our proportional fair algorithms achieve a good tradeoff between throughput and fairness. In addition, we extend our research to the physical interference model, and propose effective heuristics for solving the corresponding problems.
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