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

机译:OFDMA的多小区认知无线网络中基于免疫算法的资源分配

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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.
机译:本文研究了正交频分多址(OFDMA)的多小区认知无线电网络(CRN)中的资源分配问题。为了节省能源并提高通信效率,在优化目标中既要考虑系统吞吐量又要考虑能源效率问题,同时引入系统公平性以保持多个认知小区之间的负载均衡。考虑到认知基站(CBS)的发射功率限制以及CBS向主要用户(PU)引入的干扰功率约束等各种因素,相应的资源分配属于多目标优化类别。问题。因此,我们首先采用优化目标调整系数,以在系统吞吐量和能源效率之间做出折衷。然后,我们应用免疫算法解决了这一问题,并设计了特定的功率调节方法以保证抗体的可行性。最后,我们进行了广泛的仿真实验,数值结果表明,该算法优于注水算法。

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