Non-cooperative uplink power control in cellular radio systems
Wireless Networks - Special issue transmitter power control
A Nash game algorithm for SIR-based power control in 3G wireless CDMA networks
IEEE/ACM Transactions on Networking (TON)
Auction-based spectrum sharing
Mobile Networks and Applications
Dynamic Spectrum Access with QoS and Interference Temperature Constraints
IEEE Transactions on Mobile Computing
Cognitive radio: an information-theoretic perspective
IEEE Transactions on Information Theory
Power Control and Channel Allocation in Cognitive Radio Networks with Primary Users' Cooperation
IEEE Transactions on Mobile Computing
On cognitive radio networks with opportunistic power control strategies in fading channels
IEEE Transactions on Wireless Communications
Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks
IEEE Journal on Selected Areas in Communications
Adaptive power control for wireless networks using multiple controllers and switching
IEEE Transactions on Neural Networks
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In this paper, we propose two power adjustment methods for cognitive radio networks. In the first algorithm, the transmitter derives the transmission power with PID control in order to satisfy the QoS constraints in secondary networks. The derived transmission power is compared with a constraint condition in order to avoid the interference with primary networks, and then the actual transmission power is decided. Because the constraint condition affects the performance of our proposed method significantly, we propose an effective update algorithm. On the other hand, the second algorithm is based on model predictive control (MPC). In this method, the decision of transmission power is formulated as quadratic programming (QP) problem and the transmission power is derived directly with the constraint condition. We evaluate the performances of our proposed methods with simulation and compare the proposed methods with the distributed power control (DPC) method. In numerical examples, we show that our proposed methods are more effective than the existing method in some situations. We also prove analytically that the interference with primary networks can be avoided with probability one by using our proposed method if each transmitter has the information about every channel gain.