Energy efficiency optimization for secure transmission in MISO cognitive radio network with energy harvesting

作     者：Zhang, Miao Cumanan, Kanapathippillai Thiyagalingam, Jeyarajan Wang, Wei Burr, Alister G. Ding, Zhiguo Dobre, Octavia A. 

作者机构：School of Information Science and Technology Nantong University Nantong China Department of Electronic Engineering University of York York United Kingdom Scientific Computing Department of Rutherford Appleton Laboratory Science and Technology Facilities Council Harwell Campus Didcot United Kingdom Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China School of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom Department of Electrical and Computer Engineering Memorial University St. JohnsNLA1B 3X5 Canada 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2019年

核心收录：

主　　题：Cognitive radio 

摘      要：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. Copyright © 2019, The Authors. All rights reserved.