Throughput scheduling in cognitive radio networks based on immune optimization  

认知无线电网络中基于免疫优化的吞吐量调度（英文）

作　　者：柴争义[1,2] 郑宝林[3] 沈连丰[1] 朱思峰[1] 

机构地区：[1]东南大学移动通信国家重点实验室,南京210096 [2]天津工业大学计算机科学与软件学院,天津300384 [3]河南职业技术学院信息工程系,郑州450046

出　　处：《Journal of Southeast University(English Edition)》2015年第4期431-436,共6页东南大学学报（英文版）

基　　金：The National Natural Science Foundation of China(No.U1504613;61202099;61201175;U1204618);China Postdoctoral Science Foundation(No.2013M541586)

摘　　要：To study the throughput scheduling problem under interference temperature in cognitive radio networks, an immune algorithm-based suboptimal method was proposed based on its NP-hard feature. The problem is modeled as a constrained optimization problem to maximize the total throughput of the secondary users（ SUs）. The mapping between the throughput scheduling problems and the immune algorithm is given. Suitable immune operators are designed such as binary antibody encoding, antibody initialization based on pre-knowledge, a proportional clone to its affinity and an adaptive mutation operator associated with the evolutionary generation. The simulation results showthat the proposed algorithm can obtain about 95% of the optimal throughput and operate with much lower liner computational complexity.针对认知无线电网络中干扰温度下的吞吐量调度问题,基于问题的NP-hard特性,提出一种基于智能免疫优化的次优吞吐量调度算法.将吞吐量调度问题建模为一个最大化所有认知用户吞吐量的约束优化问题,给出了吞吐量调度问题和免疫算法的映射关系,设计了适合问题求解的二进制抗体编码方式、基于先验知识的抗体初始化方法、基于抗体亲和度的比例克隆方式及基于进化代数的变异算子.实验结果表明,所提算法可以得到大约95%的最优吞吐量,并且具有较低的线性复杂度.

关 键 词：cognitive radio networks throughput scheduling immune algorithm interference temperature 

分 类 号：TN311[电子电信—物理电子学]