A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with t...A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.展开更多
针对多波束卫星通信系统下行链路存在多个窃听者的场景,在仅已知窃听者大概位置的条件下,提出了两种鲁棒安全波束成形(beamforming,BF)方案。一种是基于卫星总发射功率受限条件下的系统安全速率最大化准则,提出了基于广义瑞利商的鲁棒B...针对多波束卫星通信系统下行链路存在多个窃听者的场景,在仅已知窃听者大概位置的条件下,提出了两种鲁棒安全波束成形(beamforming,BF)方案。一种是基于卫星总发射功率受限条件下的系统安全速率最大化准则,提出了基于广义瑞利商的鲁棒BF方案,得到了BF权矢量的解析解。另一种是基于安全速率和卫星总发射功率约束下的安全能效最大化准则,提出了一种分式规划、罚函数以及凸差(difference of convex,DC)规划理论相结合的嵌套迭代算法,完成鲁棒BF设计。仿真结果表明,跟传统的非鲁棒BF方案相比,所提出的两种鲁棒BF方案能够获得更好的安全性能。展开更多
文摘卫星通信和干扰一体化是电磁战的重要手段之一,而新兴的智能反射面(Intelligent Reflecting Surface,IRS)技术为该手段的实现提供了新思路。针对装载在太阳能帆板上IRS辅助的卫星通信系统,提出了一种基于鲁棒波束成形(Beamforming,BF)的通信和干扰一体化方法,实现卫星载荷的多功能化。建立以最小干扰功率最大化为优化目标,以地球站服务质量需求以及卫星最大发射功率为约束条件的通扰一体化优化问题。在仅已知非完美信道状态信息(Channel State Information,CSI)的条件下,将三角不等式、一阶泰勒级数展开以及S-procedure等数学方法有机结合,提出一种鲁棒BF方法,通过对该非凸问题进行求解,得到卫星阵列和IRS的波束成形权矢量以及功率分配系数。计算机仿真结果验证了所提算法的鲁棒性和优越性,实现了通信和通信干扰波形一体化设计。
基金supported by the Key International Cooperation Research Project(61720106003)the National Natural Science Foundation of China(62001517)+2 种基金the Shanghai Aerospace Science and Technology Innovation Foundation(SAST2019-095)the NUPTSF(NY220111)the Foundational Research Project of Complex Electronic System Simulation Laboratory(DXZT-JC-ZZ-2019-009,DXZTJC-ZZ-2019-005).
文摘A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.
文摘针对多波束卫星通信系统下行链路存在多个窃听者的场景,在仅已知窃听者大概位置的条件下,提出了两种鲁棒安全波束成形(beamforming,BF)方案。一种是基于卫星总发射功率受限条件下的系统安全速率最大化准则,提出了基于广义瑞利商的鲁棒BF方案,得到了BF权矢量的解析解。另一种是基于安全速率和卫星总发射功率约束下的安全能效最大化准则,提出了一种分式规划、罚函数以及凸差(difference of convex,DC)规划理论相结合的嵌套迭代算法,完成鲁棒BF设计。仿真结果表明,跟传统的非鲁棒BF方案相比,所提出的两种鲁棒BF方案能够获得更好的安全性能。
