Energy-efficient subcarrier power allocation for cognitive radio networks using statistical interference model

We study the energy-optimal subcarrier power allocation for OFDM-based cognitive radio (CR) networks. A CR transmitter communicates with CR receivers on a channel borrowed from licensed primary users (PUs) when PUs´ transmission are detected absence on those channels. Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the secondary user (SU) cause mutual-interference to each other. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. We propose iterative method based on Dinkelbach theorem using parametric objective function for the fractional programming problem. We show analytically that under a special case, the optimal power allocation follows waterfilling algorithm. Numerical results are given to show the effect of different parameters on the energy-efficiency.