This paper investigates the resource allocation for rate-splitting multiple access(RSMA)enabled multibeam satellite communication systems.Specifically,we minimize the total unmet user rate,which denotes the difference...This paper investigates the resource allocation for rate-splitting multiple access(RSMA)enabled multibeam satellite communication systems.Specifically,we minimize the total unmet user rate,which denotes the difference between the users’rate requirement and the practical achievable rate,as well as the total transmit power of the satellite by optimizing the precoding,power allocation,and rate allocation,under the per-feed power and rate constraints.To solve the non-convex optimization problem,a twostage scheme is proposed.In particular,in the first stage,we present a precoding scheme by maximizing the signal-to-leakage-plus-noise ratio of each beam to eliminate the inter-beam interference.In the second stage,we introduce auxiliary variables to obtain an upper bound on the objective function under the given precoding matrix and transform the rate constraints of the original problem into second-order cones(SOC)and linear matrix inequations(LMI).Then,the successive convex approximation(SCA)technique is used to obtain suboptimal power and rate allocation solutions.Moreover,the initial feasible solution for power allocation is provided by using the standard interior point method.Finally,numerical results verify the superiority of our proposed solution compared to the benchmark methods in terms of objective function values.展开更多
文摘This paper investigates the resource allocation for rate-splitting multiple access(RSMA)enabled multibeam satellite communication systems.Specifically,we minimize the total unmet user rate,which denotes the difference between the users’rate requirement and the practical achievable rate,as well as the total transmit power of the satellite by optimizing the precoding,power allocation,and rate allocation,under the per-feed power and rate constraints.To solve the non-convex optimization problem,a twostage scheme is proposed.In particular,in the first stage,we present a precoding scheme by maximizing the signal-to-leakage-plus-noise ratio of each beam to eliminate the inter-beam interference.In the second stage,we introduce auxiliary variables to obtain an upper bound on the objective function under the given precoding matrix and transform the rate constraints of the original problem into second-order cones(SOC)and linear matrix inequations(LMI).Then,the successive convex approximation(SCA)technique is used to obtain suboptimal power and rate allocation solutions.Moreover,the initial feasible solution for power allocation is provided by using the standard interior point method.Finally,numerical results verify the superiority of our proposed solution compared to the benchmark methods in terms of objective function values.
文摘针对用户在存在窃听者的复杂通信环境进行中继通信的安全问题,提出了一种多无人机辅助的中继通信网络为用户提供通信服务。通过基于Q混合网络(Q-mixing network,QMIX)的多智能体深度强化学习(multi-agent reinforcement learning,MRAL)算法优化无人机轨迹与功率分配,在信息安全敏感度较低用户(次要用户)最低速率得到保障的情况下,提高信息安全敏感较高用户(主要用户)的安全和速率。仿真结果表明,算法相较于双层深度Q网络(double deep Q-network,Double DQN)和对偶深度Q网络(dueling deep Q-network,Dueling DQN),累积奖励分别提高了大约15.5%和1.26%;模型的速率分割多址技术相较于空分多址和非正交多址技术,在系统整体性能和信息安全保障方面都具有显著优势,为多用户通信场景下的安全高效通信提供了更优解决方案。
