摘要
针对传统基于能量收集的全双工认知多输入多输出(MIMO)系统忽略自干扰对提高能量利用率的作用问题,建立了基于全双工MIMO的认知中继网络,通过能量收集技术进行自干扰收集.研究了系统能量效率最大化问题,在满足中继发送功率限制等约束条件下,对传输信号协方差和功率划分因子进行联合优化.利用半定松弛算法将系统优化问题转化成凸优化问题,并结合注水功率算法分析得到最优解.仿真结果表明:与传统自干扰消除模式相比,所提方案在保证系统频谱效率的同时,系统能量效率还可提高13.9%;在自干扰收集模式下,与系统容量最大化方案相比,所提方案每传输1 bit信息可降低近0.1 J的功率消耗.
In conventional full-duplex cognitive MIMO(multiple-input multiple-output) networks based on the energy harvesting,the self-interference was cancelled,which aimed to improve the spectrum efficiency.However,the role of the self-interference to improve the energy utilization was ignored. To tackle this, a cognitive relaying network based on full-duplex and MIMO was established to carry out self-interference harvesting through energy harvesting technique.The energy efficiency maximization was researched, and the transmit signal covariance matrix and the power splitting ratios were jointly designed while meeting the constraints such as the transmit power of relay.The semidefinite relaxation algorithm was introduced to convert the optimal problem into convex problem,and water-filling algorithm was also implied to derive the optimal solution.Numerical results show that the proposed scheme has 13.9% performance gain on energy efficiency over the scheme without self-interference harvesting while ensuring the spectrum efficiency.Moreover,compared with the system capacity maximization scheme,the proposed scheme can reduce 0.1 J when 1 bit of information is transmitted.
作者
鲍慧
李梦辉
赵伟
BAO Hui;LI Menghui;ZHAO Wei(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,Hebei China)
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2019年第6期17-22,共6页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(61501185)
河北省自然科学基金资助项目(F2016502062)
中央高校基本科研业务费专项资金资助项目(2015MS95)
关键词
能量收集
全双工
认知多输入多输出
自干扰收集
能量效率
energy harvesting
full-duplex
cognitive MIMO
self-interference harvesting
energy efficiency
