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Energy-Efficient Resource Allocation for Heterogeneous Cognitive Radio Networks with Femtocells

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4 Author(s)
Renchao Xie ; Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, P.R. China, and also with the Dept. of Systems and Computer Eng., Carleton University, Ottawa, ON, Canada ; F. Richard Yu ; Hong Ji ; Yi Li

Both cognitive radio and femtocell have been considered as promising techniques in wireless networks. However, most of previous works are focused on spectrum sharing and interference avoidance, and the energy efficiency aspect is largely ignored. In this paper, we study the energy efficiency aspect of spectrum sharing and power allocation in heterogeneous cognitive radio networks with femtocells. To fully exploit the cognitive capability, we consider a wireless network architecture in which both the macrocell and the femtocell have the cognitive capability. We formulate the energy-efficient resource allocation problem in heterogeneous cognitive radio networks with femtocells as a Stackelberg game. A gradient based iteration algorithm is proposed to obtain the Stackelberg equilibrium solution to the energy-efficient resource allocation problem. Simulation results are presented to demonstrate the Stackelberg equilibrium is obtained by the proposed iteration algorithm and energy efficiency can be improved significantly in the proposed scheme.

Published in:

IEEE Transactions on Wireless Communications  (Volume:11 ,  Issue: 11 )