Weighted sum rate maximization for OFDM-based cognitive radio systems

In this paper, we focus on the subcarrier and power allocation problem in the downlink of an OFDM system under the cognitive radio environment. We aim to maximize the weighted sum rate of secondary users, without causing adverse interferences to primary users. We formulate the optimization problem subject to a total transmit power constraint and interference constraints, and give the optimality conditions, from which we derive a power limited multilevel water-filling algorithm. Simulation results show that our proposed algorithm yields significant improvement in terms of weighted sum rate, and provides good convergence with low computational burden.