Resource allocation based on immune algorithm in cognitive radio networks

For the resource allocation in orthogonal frequency division multiple access (OFDMA) based cognitive radio network (CRN), there generally exist various constraints, such as the interference power introduced by cognitive users (CUs) to the primary user (PU) below a specified threshold, transmitted power constraints of CUs and discrete rates on sub-carriers, the corresponding resource allocation problem is an NP problem, thus the computationally efficient optimal algorithm cannot be found and the suboptimal algorithm should be developed. Unlike existing works, we study this kind of resource allocation problems by taking the priority of CUs into account and propose a computationally efficient suboptimal algorithm. The proposed algorithms can be decomposed into two steps: first, implementing sub-carrier allocation based on the immune algorithm; and then applying the greedy algorithm for rate adjustment on sub-carriers. We conduct extensive simulation experiments and the numerical results show that our proposed algorithm outperforms existing algorithms.