| 摘要: |
| 在蜂窝认知无线电网络（Cellular Cognitive Radio Network，CCRN）中，主用户（Primary User,PU）与次级用户(Secondary User,SU)之间缺乏通信，单独依靠传统的频谱感知技术来判断频谱接入机会存在一定的不可靠性。提出一种基于KL(Kullback-Leibler)散度与邻居关系的改进加权质心定位（KL-divergence Based Weighted Centroid Localization，KLD-WCL）算法。首先计算未知节点与锚节点接收信号强度（Received Signal Strength，RSS） 向量的 KL散度值，表征两者的邻近程度；其次，提出一种自适应邻居选择算法，针对每一个未知节点自适应地选择最优的邻居锚节点。在采用 KLD-WCL 算法获得 SU 位置信息的基础上，最终实现机会性接入授权频段的使能标签设置。所提方案有效减缓了RSS波动对于定位精度的影响，优化了邻居节点选择策略与加权方式。理论推导与实验结果表明，所提方案为CCRN中的SU定位算法提供了更为强健和良好的定位误差性能，能够有效增强蜂窝认知网络对于频谱接入的可靠性。 |
| 关键词: 蜂窝认知无线电网络(CCRN) 频谱接入 加权质心定位 KL散度 |
| DOI：10.20079/j.issn.1001-893x.240116001 |
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| 基金项目:国家自然科学基金资助项目（62371082） |
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| An Enhanced Weighted Centroid Localization Algorithmin Cellular Cognitive Networks |
| ZHANG Yan,LI Yinbo,SHEN Bin |
| (1.School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;2.Chongqing Key Laboratory of Mobile Communications Technology,Chongqing 400065,China) |
| Abstract: |
| In the cellular cognitive radio network(CCRN),due to the lack of communication between the primary user(PU) and the secondary user(SU),only relying on the traditional spectrum sensing technology to judge the spectrum access opportunity has some unreliability.The authors propose an improved weighted centroid location algorithm based on Kullback-Leibler(KL) divergence and neighbor relation(KLD-WCL).First,the KL divergence values of received signal strength(RSS) vectors of unknown nodes and anchor nodes are calculated to characterize their proximity.Then,an adaptive neighbour selection algorithm is proposed to adaptively select the optimal neighbour anchor node for each unknown node.After the KLD-WCL algorithm is used to obtain the SU location information,the enabling label setting for opportunistic access authorisation band is finally achieved.The proposed scheme effectively reduces the influence of RSS fluctuation on positioning accuracy,and the neighbor node selection strategy and weighting method are optimized.Theoretical derivation and experimental results show that the proposed scheme is superior to the traditional localization algorithm,and provides more robust and good localization error performance for the SU localization algorithm in CCRN,which can effectively enhance the reliability of the cellular cognitive network for spectrum access. |
| Key words: cellular cognitive radio network(CCRN) spectrum access weighted centroid localization KL divergence |
