摘要
传统的物理层安全通信只研究信息的安全传输或者系统的能量消耗,而这两者相互冲突且越来越难以满足人们对无线通信系统的高要求,因此寻求有效均衡两者的方法成为无线通信系统设计的关键。在多输入单输出(MISO)的下行网络中,联合优化接收端的安全速率和发送端的功率消耗,提出了一种基于加权切比雪夫方法的多目标优化框架(MOO),将两个冲突的单目标问题转化为一个多目标优化问题(MOOP)。引入泰勒级数展开,将非凸问题线性化;运用S-Procedure和柯西施瓦兹不等式,处理半无限约束。在发送端对信道状态信息(CSI)不完全已知的情况下,所提出的鲁棒性迭代算法,获得了安全速率和功率消耗的帕累托最优边界。实验结果表明,所提出的算法优于传统的非鲁棒性算法。
Either the security transmission of information or the energy consumption of systems is investigated in traditional physical secu- rity communication. It is of great significance to seek effective ways to balance them because of their conflicting performances and the fact that it is more and more difficult to meet people＇ s high requirements of the wireless communication system. The optimization of the trans-mit power and the secrecy rate jointly is considered in a Multiple-Input-Single-Output （MISO） downlink network. A Multi-Objective Optimization （MOO） framework based on the weighted Tchebycheff approach is proposed to transform the two conflicting single-objec- tive problems into a multi-objective problem. Taylor series expansion is then employed to recast the formulated Multi-Objective Optimi- zation Problem （MOOP） as a linear one. S-Procedure and Cauchy-Schwarz inequality are applied to deal with the semi-infinite con- straints. Finally, a robust iterative algorithm is proposed to achieve the Pareto optimal boundary under the assumption that the Channel State Information （CSI） is not perfectly known at the transmitter. Simulation results that the proposed algorithm not only demonstrates the convergence, but also indicates the effectiveness of it compared with traditional non-robust one.
出处
《计算机技术与发展》
2017年第5期183-187,191,共6页
Computer Technology and Development
基金
国家自然科学基金资助项目(61271232)
国家移动通信研究实验室开放研究基金(2012D05)
