Channel Allocation and Power Control Based on Differential Evolution Algorithm in Cognitive Radio Mesh Network

JIA Jie; LI Yan-yan; CHEN Jian; WANG Xing-wei

doi:10.3969/j.issn.0372-2112.2013.01.012

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Channel Allocation and Power Control Based on Differential Evolution Algorithm in Cognitive Radio Mesh Network

更新时间：2025-07-16

- Channel Allocation and Power Control Based on Differential Evolution Algorithm in Cognitive Radio Mesh Network
- Acta Electronica Sinica Vol. 41, Issue 1, Pages: 62-67(2013)
- 作者机构：
  
  东北大学信息科学与工程学院,辽宁,沈阳,110819
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.60903159, No.61070162, No.61173153, No.71071028, No.70931001);China Postdoctoral Science Foundation (No.20110491508, No.2012T50248);Fundamental Research Funds for the Central Universities (No.N110404014, No.N110318001);Research Fund for the Doctoral Program of Higher Education of China (No.20070145017)
- DOI：10.3969/j.issn.0372-2112.2013.01.012
  CLC： TP393
- Published：2013
- 稿件说明：
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JIA Jie, LI Yan-yan, CHEN Jian, et al. Channel Allocation and Power Control Based on Differential Evolution Algorithm in Cognitive Radio Mesh Network[J]. Acta Electronica Sinica, 2013, 41(1): 62-67.
DOI：

JIA Jie, LI Yan-yan, CHEN Jian, et al. Channel Allocation and Power Control Based on Differential Evolution Algorithm in Cognitive Radio Mesh Network[J]. Acta Electronica Sinica, 2013, 41(1): 62-67. DOI： 10.3969/j.issn.0372-2112.2013.01.012.

摘要

信道分配对于提高认知无线网状网性能具有重要作用.考虑到节点功率对网络干扰的影响

定义了网络干扰边及潜在干扰边

通过量化通信功率控制等级

给出了联合功率控制与信道分配的网络模型.提出一种基于差分演化的功率控制与信道分配算法

设计了实数编码规则及相应的约束控制机制以保证个体的有效性

确保算法的快速收敛.一系列仿真实验表明本文算法的有效性.

Abstract

Channel allocation plays an important role in improving the performance of cognitive radio mesh network.Considering the influnce of the node power on network interference

the network interference edge and potential interference edge are defined.By quantizing the level for communication power

a network model of joint power control and channel assignment is presented.Futher

the channel allocation algrithm with power control on the basis of differential evolution algorithm is proposed.The real-number encoding rules and relevant constraints control mechanisms are designed to ensure the effectiveness of the individuals

thus to converge faster to optimal solution.Extensive simulations have been performed to validate the effectiveness of the proposed algorithm.

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