Resource Allocation Based on Immune Algorithm in Multi-Cell Cognitive Radio Networks with OFDMA

This paper studies the problem of resource allocation in multi-cell cognitive radio networks (CRNs) with orthogonal frequency division multiple access (OFDMA). In order to save energy as well as improve communication efficiency, both the issues of system throughput and energy efficiency need to be considered in the optimizing objective, meanwhile, the system fairness is introduced to keep load balancing among multiple cognitive cells. Taking into account the various factors, such as the transmitting power limit of cognitive base stations (CBSs) and the constraint of interference power introduced by CBSs to the primary user (PU), the corresponding resource allocation belongs to the category of multi-objective optimization problems. Consequently, we first adopt the optimization objective adjustment coefficient to make a compromise between the issues of system throughput and energy efficiency. Then, we apply the immune algorithm to solve this problem and design the specific power adjustment method to guarantee the feasibility of antibodies. Finally, we conduct extensive simulation experiments and the numerical results show that our proposed algorithm outperforms the water-filling algorithm.