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作 者:那曦丹 张杭 秦媛 马宁[3] 胡航 NA Xidan;ZHANG Hang;QIN Yuan;MA Ning;HU Hang(Army Engineering University of PLA,Nanjing Jiangsu 210007,China;Unit 32117 of PLA,Baishan Jilin 134600,China;Unit 78167 of PLA,Chengdu Sichuan 610500,China;College of Information and Navigation,Air Force Engineering University,Xi’an Shaanxi 710100,China)
机构地区:[1]中国人民解放军陆军工程大学,江苏南京210007 [2]中国人民解放军32117部队,吉林白山134600 [3]中国人民解放军78167部队,四川成都610500 [4]中国人民解放军空军工程大学信息与导航学院,陕西西安710100
出 处:《通信技术》2024年第6期569-578,共10页Communications Technology
基 金:陕西省自然科学基础研究计划(2024JC-YBMS-514)。
摘 要:为实现边境地区无线传感网长期工作,采用无人机与非正交多址(Non-Orthogonal Multiple Access,NOMA)技术结合的网络对分布在狭长边境线的传感器进行数据采集,以有效降低无线传感网(Wireless Sensor Networks,WSNs)的能耗。传感器用户组以多载波NOMA方式上传数据至无人机,在最大发射功率、用户服务质量(Quality of Service,QoS)及无人机移动性的约束下,通过优化传感器用户调度和分组、发射功率及无人机轨迹最小化所有传感器总能耗。该优化问题为混合整数非线性优化问题,将其分解为3个子问题求解。利用穷举搜索、拉格朗日对偶分解和逐次凸逼近(Successive Convex Approximation,SCA)依次求解各子问题并迭代优化,得到能耗最小值。仿真结果表明,所提方案可以有效降低无线传感网总能耗。In order to achieve the long-term work of the wireless sensor network in the border area,a network combining UAV and NOMA(Non-Orthogonal Multiple Access)technology is used to collect data from sensors distributed along the narrow border,so as to effectively reduce the energy consumption of WSNs(Wireless Sensor Networks).The sensor user group uploads data to UAV in a multi-carrier NOMA mode to minimize the total energy consumption of all sensors by optimizing sensor user scheduling and grouping,transmit power and UAV trajectory under the constraints of maximum transmit power,user QoS(Quality of Service)and UAV mobility.The optimization problem is a mixed integer nonlinear optimization problem,which is decomposed into three subproblems to solve.By using exhaustive search,Lagrange duality decomposition and SCA(Successive Convex Approximation),the subproblems are solved successively,and the minimum energy consumption is achieved.Simulation results indicate that the proposed scheme can effectively reduce the total energy consumption of the WSNs.
关 键 词:数据采集 无人机 多载波NOMA 功率优化 轨迹优化
分 类 号:TN929.5[电子电信—通信与信息系统]
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