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作 者:张宇杰 张晓红 常春波[1,2] 郭亚君 ZHANG Yujie;ZHANG Xiaohong;CHANG Chunbo;GUO Yajun(College of Electronic Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;Institute of Industrial and Systems Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;Department of Transportation Engineering,Shanxi Vocation al College of Engineering,Taiyuan 030001,China)
机构地区:[1]太原科技大学电子信息工程学院,山西太原030024 [2]太原科技大学工业与系统工程研究所,山西太原030024 [3]山西工程职业学院交通工程系,山西太原030001
出 处:《科技创新与生产力》2025年第4期92-95,共4页Sci-tech Innovation and Productivity
基 金:国家自然科学基金项目(72071183);山西省科技创新人才团队项目(202304051001032);山西省自然科学基金项目(202203021211194)。
摘 要:本研究针对物理小区识别码(PCI)规划与优化问题,构建了一个以降低测量报告(MR)数据为目标的多目标、多约束PCI规划模型。首先,利用MapInfo工具对目标区域进行精细建模;其次,通过综合运用多种算法,在较短时间内筛选出最优方案,实现了PCI分配的高效优化;最后,基于Atoll平台中的Aster传播模型,对优化前后基站进行仿真分析,评估了切换成功率、LTE覆盖率、平均RSRP及平均SINR等关键指标。实验结果表明,所提出的群体智能算法平台在快速确定PCI规划最优方法及最优PCI规划问题中具有显著优势,并为实际网络规划提供了理论与方法上的有力支持。This study constructs a multi-objective,multi constraint physical community identification codes(PCI)planning model with the goal of reducing measurement report(MR)data for the planning and optimization of PCI.Firstly,MapInfo tool is used to finely model the target area;secondly,by comprehensively utilizing multiple algorithms,the optimal solution is selected in a relatively short period of time,achieving efficient optimization of PCI allocation;finally,based on the Aster propagation model in the Atoll platform,simulation analysis is conducted on the base stations before and after optimization to evaluate key indicators such as handover success rate,LTE coverage,average RSRP,and average SINR.The experimental results show that the proposed swarm intelligence algorithm platform has significant advantages in quickly determining the optimal method and problem for PCI planning,and provides strong theoretical and methodological support for practical network planning.
分 类 号:TN929.5[电子电信—通信与信息系统] TP301.6[电子电信—信息与通信工程] TP391.9[自动化与计算机技术—计算机系统结构]
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