MIMO中继下行通信系统中的多目标优化设计  

Multi-objective optimization design for MIMO relay downlink systems

作　　者：代延梅 吴苏[1] 

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003

出　　处：《电视技术》2017年第1期58-63,共6页Video Engineering

基　　金：国家自然科学基金项目(61271232);国家移动通信研究实验室开放研究基金(2012D05)

摘　　要：针对通信系统中系统功率消耗和接收信号均方误差(MSE)存在冲突关系,无法同时达到性能最优的情况,采用多目标优化(MOO)框架联合优化系统功率消耗和接收信号MSE。文中考虑两跳的多入多出(MIMO)放大转发(AF)中继下行通信系统。联合优化形成的多目标优化问题是非凸且难以直接求解的,为此,提出一种基于帕累托最优策略的资源分配方法,该方法采用加权切比雪夫法,并引入中继预编码矩阵的一般结构和Schur补引理将优化问题转化为SDP问题。仿真结果验证了所提出方法的有效性,表明其具有更好的性能,同时也给出了系统功耗和MSE性能之间的帕累托最优边界。As the coupled and even conflicting relationship between the system power consumption and the minimum mean-squared error （MSE） at the receiver, a multi-objective optimization （MOO） framework for optimizing system power consumption and MSE jointly is adopted. A two-hop multiple-input multiple-output （MIMO） amplify-forward （AF） relay downlink system is considered in this paper. Since the formulated MOO problem （MOOP） is non-convex and hard to tackle, a Pareto resource allocation method is proposed by exploiting the weighted Tchebycheff approach, the optimal structure of the relay precoding matrix and the Schur complement. Simulation results not only demonstrate the effectiveness of the proposed algorithm, but also unveil an important trade- off between power consumption and MSE at the receiver.

关 键 词：多入多出(MIMO) 多目标优化(MOO) 放大转发中继 最小化均方误差(MMSE) 

分 类 号：TN929.5[电子电信—通信与信息系统]