[1] Chai Zhengyi, Zheng Baolin, Shen Lianfeng, et al. Throughput scheduling in cognitive radio networksbased on immune optimization [J]. Journal of Southeast University (English Edition), 2015, 31 (4): 431-436. [doi:10.3969/j.issn.1003-7985.2015.04.001]

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Throughput scheduling in cognitive radio networksbased on immune optimization()

认知无线电网络中基于免疫优化的吞吐量调度

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

31

Issue:

2015 4

Page:

431-436

Research Field:

Electronic Science and Engineering

Publishing date:

2015-12-30

Info

Title:

Throughput scheduling in cognitive radio networksbased on immune optimization

认知无线电网络中基于免疫优化的吞吐量调度

Author(s):

Chai Zhengyi¹;  2;  Zheng Baolin³;  Shen Lianfeng¹;  Zhu Sifeng¹

¹National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
²School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300384, China
³Department of Information Engineering, Henan Vocational and Technical College, Zhengzhou 450046, China

柴争义¹;  2;  郑宝林³;  沈连丰¹;  朱思峰¹

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

Keywords:

cognitive radio networks;  throughput scheduling;  immune algorithm;  interference temperature

认知无线电网络;  吞吐量调度;  免疫算法;  干扰温度

PACS:

TN311

DOI:

10.3969/j.issn.1003-7985.2015.04.001

Abstract:

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 show that 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.

References:

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Memo

Memo:

Biography: Chai Zhengyi(1976—), male, doctor, associate professor, super_chai@126.com.
Foundation items: The National Natural Science Foundation of China(No.U1504613, 61202099, 61201175, U1204618), China Postdoctoral Science Foundation(No.2013M541586).
Citation: Chai Zhengyi, Zheng Baolin, Shen Lianfeng, et al. Throughput scheduling in cognitive radio networks based on immune optimization[J].Journal of Southeast University(English Edition), 2015, 31(4):431-436.[doi:10.3969/j.issn.1003-7985.2015.04.001]

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