Energy efficient resource allocation based on relay selection and subcarrier pairing with channel uncertainty in cognitive radio network

Abstract

More and more mobile devices join in the wireless networks, it has become a challenging problem how to mitigating the interferences and improving the energy efficiency in dynamic wireless communication environment. In this paper, a robust resource allocation algorithm is proposed to maximize the energy efficiency (EE) in a multi-carrier decode-and-forward (DF) cognitive radio(CR) relay network, which subjects to multiple constraints in aspects of relay transmit power, signal to noise ratio threshold, subcarrier pairing, relay selection and the primary user’s minimum transmit rate requirement. The original optimization problem is non-convex with consideration of the channel uncertainty, and it is the mixed binary integer programming problem. Subsequently, we use the worst-case method to deal with channel uncertainty and convert the original non-convex problem into a quasi-concave problem by the Dinkelbach method. We solve the NP-hard problem in two steps: fixing the subcarriers to get the optimal relay selection and allocating the subcarriers according to the optimal relay selection. By using the method of dual decomposition, we get the approximate optimal solution of the problem. Simulation results show that the proposed joint resource allocation scheme guarantees the desired service quality requirements, and the energy-efficiency obtained is improved comparing with some existing works. In addition, the proposed resource allocation algorithm shows better convergence performance under different topologies, which validates the resource allocation scheme has good scalability.