针对智能反射面(Intelligent Reflecting Surface,IRS)辅助的含窃听者的认知物联网(Cognitive Internet of Things,C-IoT)通信系统,提出了一种基于联合波束成型的保密率优化方案。在系统模型中,考虑了一个由发射机、主用户、次用户、窃...针对智能反射面(Intelligent Reflecting Surface,IRS)辅助的含窃听者的认知物联网(Cognitive Internet of Things,C-IoT)通信系统,提出了一种基于联合波束成型的保密率优化方案。在系统模型中,考虑了一个由发射机、主用户、次用户、窃听者和智能反射面组成的多输入单输出通信场景。基于该模型,构建保密率优化问题,即在发射机总功率约束、主用户端干扰功率约束以及智能反射面单位模约束的条件下,通过联合优化主被动波束成型,最大化系统的保密率(Secrecy Rate,SR)。在实现过程中,由于公式化的问题非凸,因此使用交替优化的方法将原始问题分解为两个子问题进行优化,即发射机波束成型矩阵的优化以及IRS相移矩阵优化。针对发射机波束成型的矩阵优化,使用半定松弛法与逐次凸逼近法。接着,使用丁克尔巴赫法与逐次凸逼近的方法对IRS的相移矩阵进行优化。仿真结果表明,在含有窃听者的多输入单输出系统中,引入智能反射面实现主被动波束成型的优化有效提高了系统的保密率。展开更多
针对多输入多输出认知物联网(C-IoT:Cognitive Internet of Things)系统中出现的高能耗问题,提出了一种基于智能反射面(IRS:Intelligent Reflecting Surface)辅助的联合波束形成优化算法。以次用户处的信干噪比和IRS处的离散相移为约束...针对多输入多输出认知物联网(C-IoT:Cognitive Internet of Things)系统中出现的高能耗问题,提出了一种基于智能反射面(IRS:Intelligent Reflecting Surface)辅助的联合波束形成优化算法。以次用户处的信干噪比和IRS处的离散相移为约束条件,构建新的优化准则,通过联合优化次发射机处的主动波束形成矩阵和IRS处的被动波束形成矩阵最大化系统的能量效率。将复杂的非凸优化问题分解为子问题,分别使用定点迭代法和逐次细化法对子问题进行处理。仿真结果表明,在多天线场景下所提算法具有良好的收敛性。与基准方案相比,所提算法在多用户情况下有效提高了系统的能量效率。展开更多
The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless cove...The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.展开更多
文摘针对智能反射面(Intelligent Reflecting Surface,IRS)辅助的含窃听者的认知物联网(Cognitive Internet of Things,C-IoT)通信系统,提出了一种基于联合波束成型的保密率优化方案。在系统模型中,考虑了一个由发射机、主用户、次用户、窃听者和智能反射面组成的多输入单输出通信场景。基于该模型,构建保密率优化问题,即在发射机总功率约束、主用户端干扰功率约束以及智能反射面单位模约束的条件下,通过联合优化主被动波束成型,最大化系统的保密率(Secrecy Rate,SR)。在实现过程中,由于公式化的问题非凸,因此使用交替优化的方法将原始问题分解为两个子问题进行优化,即发射机波束成型矩阵的优化以及IRS相移矩阵优化。针对发射机波束成型的矩阵优化,使用半定松弛法与逐次凸逼近法。接着,使用丁克尔巴赫法与逐次凸逼近的方法对IRS的相移矩阵进行优化。仿真结果表明,在含有窃听者的多输入单输出系统中,引入智能反射面实现主被动波束成型的优化有效提高了系统的保密率。
文摘针对多输入多输出认知物联网(C-IoT:Cognitive Internet of Things)系统中出现的高能耗问题,提出了一种基于智能反射面(IRS:Intelligent Reflecting Surface)辅助的联合波束形成优化算法。以次用户处的信干噪比和IRS处的离散相移为约束条件,构建新的优化准则,通过联合优化次发射机处的主动波束形成矩阵和IRS处的被动波束形成矩阵最大化系统的能量效率。将复杂的非凸优化问题分解为子问题,分别使用定点迭代法和逐次细化法对子问题进行处理。仿真结果表明,在多天线场景下所提算法具有良好的收敛性。与基准方案相比,所提算法在多用户情况下有效提高了系统的能量效率。
文摘The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.
