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2020, 02, 30-35+69
非对称全双工双向中继系统能效研究
基金项目(Foundation): 国家自然科学基金项目(61401238,61871241);; 江苏省高校自然科学基金项目(18KJB510037);; 南通大学-南通智能信息技术联合研究中心开放课题(KFKT2017A03);; 南通市科技计划项目(MS12018083,JC2018127,JC2019114)
邮箱(Email):
DOI: 10.12194/j.ntu.20190521001
摘要:

研究了频率非选择性瑞利衰落信道中,具有不对称业务特性的全双工双向中继系统能效问题,其中两个源节点在不同信息发送速率情况下,借助全双工中继节点进行消息的互通。基于解码转发中继策略,在瑞利衰落信道环境下,将能效优化问题转化为一个递进式两阶段优化子问题:首先固定传输时间,优化各个传输节点的发射功率;再对传输时间进行优化,从而给出能效优化问题的闭式解。基于此解,提出一种最小化系统总发射功率的节点功率控制和传输时间分配的联合实现算法,并通过数值仿真实验验证了所提算法的有效性。仿真结果表明:在源节点具有不对称业务情况下,所提算法具有能效性能优势,并随着业务不对称度的提高,能效性能优势越加显著,在强不对称业务情形下,比"仅发射功率控制"算法可节约60 dB总发射功率。

Abstract:

The energy efficient optimization problem of full-duplex bidirectional relaying with asymmetric traffics is investigated in frequency non-selective Rayleigh fading channels, where two source nodes employ a full-duplex relay node to exchange messages with different data-rates. Based on the decode-and-forward strategy, the energy efficient optimization problem is transformed into a two-stage optimization sub-problem. First, the transmission-time of the two stages is fixed, the transmit power of the nods is optimized. Then, optimal solution of the transmission-time of the two stages is studied. On this basis, the closed-form solution to energy efficient optimization problem is presented.Then, a joint implementation algorithm for power control of terminals and transmission-time allocation minimizing the total transmit power of the system is proposed. The simulation experiments reveal that the proposed algorithm performs well in terms of energy efficiency when the source nodes have asymmetric traffics. Meanwhile, the performance improvement becomes more evident with increasing the level of traffic asymmetry. For the strongly asymmetric traffic case, the proposed algorithm can obtain the saving of 60 dB energy compared with the scheme of only controlling the transmit power of the nodes.

参考文献

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基本信息:

DOI:10.12194/j.ntu.20190521001

中图分类号:TN911.22

引用信息:

[1]钱冲,吉晓东,田培胜.非对称全双工双向中继系统能效研究[J],2020(02):30-35+69.DOI:10.12194/j.ntu.20190521001.

基金信息:

国家自然科学基金项目(61401238,61871241);; 江苏省高校自然科学基金项目(18KJB510037);; 南通大学-南通智能信息技术联合研究中心开放课题(KFKT2017A03);; 南通市科技计划项目(MS12018083,JC2018127,JC2019114)

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