Admission control and interference management in dynamic spectrum access networks
EURASIP Journal on Wireless Communications and Networking - Special issue on dynamic spectrum access: from the concept to the implementation
Cognitive radios for dynamic spectrum access: from concept to reality
IEEE Wireless Communications
Analysis of optimal random access policies for cognitive radio networks under Rayleigh fading
Proceedings of the 6th International Conference on Queueing Theory and Network Applications
Performance Comparison of Two Channel Allocation Strategies in Cellular Networks
Wireless Personal Communications: An International Journal
Media access protocol for a coexisting cognitive femtocell network
Computer Networks: The International Journal of Computer and Telecommunications Networking
Distributed power adjustment based on control theory for cognitive radio networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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We consider a point-to-multipoint cognitive radio network that shares a set of channels with a primary network. Within the cognitive radio network, a base station controls and supports a set of fixed-location wireless subscribers. The objective is to maximize the throughput of the cognitive network while not affecting the performance of primary users. Both downlink and uplink transmission scenarios in the cognitive network are considered. For both scenarios, we propose two-phase mixed distributed/centralized control algorithms that require minimal cooperation between cognitive and primary devices. In the first phase, a distributed power updating process is employed at the cognitive and primary nodes to maximize the coverage of the cognitive network while always maintaining the constrained signal to interference plus noise ratio of primary transmissions. In the second phase, centralized channel assignment is carried out within the cognitive network to maximize its throughput. Numerical results are obtained for the behaviors and performance of our proposed algorithms.