Aggregation-aware resource allocation for cognitive radio networks

In this paper, we investigate the dynamic spectrum aggregation and allocation problem in multiuser orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks. We first study a spectrum aggregation (SA)-based spectrum assignment algorithm, which enables secondary users (SUs) to gather multiple spectrum fragments into one channel to support high bandwidth requirement, to improve the spectrum utilization efficiency for the considered system. Then we aim to maximize the system capacity of the considered CR network while considering many practical limitations, such as minimal rate requirement of SUs, transmission power budget and interference constraints of the system. Since the formulated optimization task is a challenging mixed integer programming problem that is NP-hard, a user-oriented subcarrier allocation algorithm is introduced to remove the integer constraints and then for a given subchannels assignment, a fast barrier method is developed to tackle the optimal power allocation problem, the key of which is to calculate Newton step with approximate linear complexity instead of 0{N3) in standard method. Simulation results validate that our algorithm is significantly better than the standard technique and can maximize the sum capacity of the system.