CRAHNs: Cognitive radio ad hoc networks
Ad Hoc Networks
Inertia-based distributed channel allocation
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Distributed channel assignment in cognitive radio networks
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Joint power and channel allocation based on fair sharing in cognitive radio system
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Cognitive interference management in retransmission-based wireless networks
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
IEEE Transactions on Signal Processing
GADIA: A greedy asynchronous distributed interference avoidance algorithm
IEEE Transactions on Information Theory
Optimizing spectrum trading in cognitive mesh network using machine learning
Journal of Electrical and Computer Engineering - Special issue on Resource Allocation in Communications and Computing
Spectrum Sharing in Competing Wireless Systems: A Simulation Study Using WLAN and WMAN
Journal of Network and Systems Management
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Dynamic spectrum access is a promising technique to use spectrum efficiently. Without being restricted to any prefixed spectrum bands, nodes choose operating spectrum on-demand. Such flexibility, however, makes efficient and fair spectrum access in large-scale networks a great challenge. Prior work in this area focused on explicit coordination where nodes communicate with peers to modify local spectrum allocation, and may heavily stress the communication resource. In this paper, we introduce a distributed spectrum management architecture where nodes share spectrum resource fairly by making independent actions following spectrum rules. We present five spectrum rules to regulate node behavior and maximize system fairness and spectrum utilization, and analyze the associated complexity and overhead. We show analytically and experimentally that the proposed rule-based approach achieves similar performance with the explicit coordination approach, while significantly reducing communication cost.