Energy Efficiency Optimization for Secure Transmission in MISO Cognitive Radio Network with Energy Harvesting

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

Max-min Fair Wireless Energy Transfer for Secure Multiuser Communication Systems

This paper considers max-min fairness for wireless energy transfer in a downlink multiuser communication system. Our resource allocation design maximizes the minimum harvested energy among multiple multiple-antenna energy harvesting receivers (potential eavesdroppers) while providing quality of service (QoS) for secure communication to multiple single-antenna information receivers. In particular, the algorithm design is formulated as a non-convex optimization problem which takes into account a minimum required signal-to-interference-plus-noise ratio (SINR) constraint at the information receivers and a constraint on the maximum tolerable channel capacity achieved by the energy harvesting receivers for a given transmit power budget. The proposed problem formulation exploits the dual use of artificial noise generation for facilitating efficient wireless energy transfer and secure communication. A semidefinite programming (SDP) relaxation approach is exploited to obtain a global optimal solution of the considered problem. Simulation results demonstrate the significant performance gain in harvested energy that is achieved by the proposed optimal scheme compared to two simple baseline schemes.Comment: 5 pages, invited paper, IEEE Information Theory Workshop 2014, Hobart, Tasmania, Australia, Nov. 201

Robust AN-Aided Beamforming Design for Secure MISO Cognitive Radio Based on a Practical Nonlinear EH Model

Energy harvesting techniques are promising in next generation wireless communication systems. However, most of the existing works are based on an ideal linear energy harvesting model. In this paper, a multiple-input single-output cognitive radio network is studies under a practical non-linear energy harvesting model. In order to improve the security of both the primary network and the secondary network, a cooperative jamming scheme is proposed. A robust artificial noise aided beamforming design problem is formulated under the bounded channel state information error model. The formulated problem is non-convex and challenging to be solved. Using S-procedure and the semidefinite relaxation method, a suboptimal beamforming can be obtained. Simulation results show that the performance achieved under the non-linear energy harvesting model may be better than that obtained under the linear energy harvesting model. It is also shown that the cooperation betwen the primary network and the secondary network can obtain a performance gain compared with that without this cooperation