Energy Efficiency Optimization for Secure Transmission in MISO Cognitive Radio Network With Energy Harvesting
Energy Efficiency Optimization for Secure Transmission in MISO Cognitive Radio Network With Energy Harvesting
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DOI：
10.1109/access.2019.2938874
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发表时间：
2019-08
期刊：
影响因子：
3.9
通讯作者：
Miao Zhang;K. Cumanan;Jeyarajan Thiyagalingam;Wei Wang;A. Burr;Z. Ding;O. Dobre
中科院分区：
文献类型：
--
作者：
Miao Zhang;K. Cumanan;Jeyarajan Thiyagalingam;Wei Wang;A. Burr;Z. Ding;O. Dobre
在本文中，我们研究了不同的保密能量效率（SEE）优化问题的多输入单输出的认知无线电（CR）网络中存在的能量收集接收机。特别是，这些能源效率的设计开发与不同的假设信道状态信息（CSI）在发射机，即完美的CSI，统计CSI和不完美的CSI与有界信道不确定性。特别地，这里的首要目标是设计一种波束成形技术，该技术最大化SEE，同时满足与发射器和接收器之间的干扰和收获能量相关的所有相关约束。我们表明，原来的问题是非凸的，他们的解决方案是棘手的。通过使用一些技术，如非线性分式规划和凹（DC）函数的差异，我们重新制定原来的问题，使他们易于处理。然后，我们结合联合收割机这些技术与Dinkelbach的算法，推导出迭代算法，以确定相关的波束形成向量，导致SEE最大化。在此基础上，利用半定松弛、非线性分式规划和S-过程将原问题映射为一系列半定规划，研究了椭球有界信道不确定性下的鲁棒设计问题。此外，我们表明，最大的SEE可以通过在一维空间中的搜索算法来实现。数值结果，与文献中现有的技术相比，所提出的设计SEE最大化的有效性。
In this paper, we investigate different secrecy energy efficiency (SEE) optimization problems in a multiple-input single-output underlay cognitive radio (CR) network in the presence of an energy harvesting receiver. In particular, these energy efficient designs are developed with different assumptions of channels state information (CSI) at the transmitter, namely perfect CSI, statistical CSI and imperfect CSI with bounded channel uncertainties. In particular, the overarching objective here is to design a beamforming technique maximizing the SEE while satisfying all relevant constraints linked to interference and harvested energy between transmitters and receivers. We show that the original problems are non-convex and their solutions are intractable. By using a number of techniques, such as non-linear fractional programming and difference of concave (DC) functions, we reformulate the original problems so as to render them tractable. We then combine these techniques with the Dinkelbach’s algorithm to derive iterative algorithms to determine relevant beamforming vectors which lead to the SEE maximization. In doing this, we investigate the robust design with ellipsoidal bounded channel uncertainties, by mapping the original problem into a sequence of semidefinite programs by employing the semidefinite relaxation, non-linear fractional programming and S-procedure. Furthermore, we show that the maximum SEE can be achieved through a search algorithm in the single dimensional space. Numerical results, when compared with those obtained with existing techniques in the literature, show the effectiveness of the proposed designs for SEE maximization.