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一种基于无线电环境地图的路由优化机制
引用本文:朱 江,雷 云,刘亚利.一种基于无线电环境地图的路由优化机制[J].国际商务研究,2018,58(9).
作者姓名:朱 江  雷 云  刘亚利
作者单位:重庆邮电大学 移动通信技术重庆市重点实验室,重庆400065,重庆邮电大学 移动通信技术重庆市重点实验室,重庆400065,重庆邮电大学 移动通信技术重庆市重点实验室,重庆400065
基金项目:国家自然科学基金资助项目(61102062)
摘    要:设计认知无线网络路由算法时,需要兼顾主用户保护与路由性能两个方面。为了提高认知无线网络中次用户之间路由的端到端性能,提出了基于无线电环境地图的路由优化机制,该机制中无线电环境地图能够为次用户提供主用户保护有关的无线电环境数据。首先,无线电环境地图根据次用户的数据请求将各授权频段的可用概率与功率控制相关信息反馈到该次用户;其次,次用户可以计算出与上一跳次用户之间的链路稳定性以及传输时延;最后,目的次用户通过计算每条路由的端到端吞吐量的期望值,然后选取期望值最大的一条路由。仿真结果表明,该路由机制在平均分组投递率、平均端到端吞吐量、平均端到端时延方面均优于对比路由算法。

关 键 词:认知无线网路  无线电环境地图  路由优化  端到端吞吐量

A routing optimization mechanism based on radio environment map in cognitive wireless networks
ZHU Jiang,LEI Yun and LIU Yali.A routing optimization mechanism based on radio environment map in cognitive wireless networks[J].International Business Research,2018,58(9).
Authors:ZHU Jiang  LEI Yun and LIU Yali
Institution:Chongqing Key Laboratory of Mobile Communications Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China,Chongqing Key Laboratory of Mobile Communications Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China and Chongqing Key Laboratory of Mobile Communications Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
Abstract:In designing routing algorithm for cognitive radio networks(CRNs),it necessary to take into account both the main user protection and routing performance.In order to improve the end-to-end performance of routing between secondary users in CRNs,a routing optimization mechanism based on radio environment map is proposed.In this scheme,the radio environment map provides secondary users with radio environment data related to primary user protection.Firstly,the radio environment map feeds back to the secondary user the available probability and power control related information of each licensed frequency band according to the data request of the secondary user.Secondly,the secondary user calculates the link stability with the user with the last hop.Finally,the destination user calculates the expected end-to-end throughput of each route,and then selects the route with the highest expected value.Simulation results show that the routing mechanism outperforms the comparative routing algorithm in average packet delivery rate,average end-to-end throughput and average end-to-end delay.
Keywords:cognitive  radio network(CRN)  radio environment map  route optimization  end-to-end throughput
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