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移动加权质心定位(MWCL)算法是对传统网络中质心定位算法的改进。为了满足认知无线电网络中主用户的非合作特性,移动加权质心定位算法不需要主用户与认知用户合作。针对质心定位算法的定位精度主要取决于认知用户的密度和分布,移动加权质心定位算法利用认知用户的移动特性,提高认知用户的密度,并且设计了移动路径的规划方法;利用接收信号强度对认知用户坐标进行加权,克服了认知用户分布不均匀对定位精度带来的影响。根据认知用户密度、用户密度、连通门限三种参数,对移动加权质心定位算法的性能进行了分析。实验结果表明,移动加权质心定位算法的定位误差比质心定位算法降低了50%～60%。
The mobile weighted centroid location (MWCL) algorithm is an improvement of the centroid location algorithm in traditional networks. In order to meet the non-cooperative characteristics of the primary user in the cognitive radio network, the mobile weighted centroid positioning algorithm does not need the cooperation of the primary user and the cognitive user. The positioning accuracy of the centroid localization algorithm mainly depends on the density and distribution of cognitive users. The mobile weighted centroid localization algorithm uses the cognitive characteristics of mobile users to improve the cognitive user’s density, and the design of the mobile path planning method; using the received signal The intensity of cognitive user coordinates weighted to overcome the uneven distribution of cognitive users on the positioning accuracy. According to three parameters of cognitive user density, user density and connectivity threshold, the performance of mobile weighted centroid location algorithm is analyzed. Experimental results show that the positioning error of the moving weighted centroid location algorithm is reduced by 50% -60% compared with the centroid location algorithm.