Spectrum aggregation based spectrum allocation for cognitive radio networks

In cognitive radio networks, the available spectrum holes are usually discontinuous. Hence, it is hard to exploit these spectrum holes because the bandwidth of an individual one may not be able to satisfy the wide bandwidth requirement imposed by secondary users (SUs). Spectrum aggregation (SA) enables SUs to integrate several spectrum holes into one channel with wide bandwidth which may support high bandwidth requirement. In this paper, we investigate the problem of SA based spectrum allocation. Specifically, we cast this problem into Multiple Knapsack Problems (MKP). Based on this scheme, we propose a spectrum aggregation algorithm to maximize the available bandwidth that SUs can access, as well as two spectrum allocation algorithms including an optimal algorithm and a suboptimal one. The proposed algorithms are evaluated in terms of total available bandwidth and spectrum utilization efficiency. Numerical results show that the proposed algorithms can significantly outperform the existing algorithms.