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International Conference on Computer Networks and Communication Technology (CNCT)

Joint Beamforming and the Artificial Noise Security Scheme Based on Successive Convex Approximation in Multi-relay Cognitive Network

Xianzhong Xie, Xiang-yu XIE, Shu Tang, Jiu-jiu CHEN

Published Jan 1, 2017• 0 citations
Publisher

Abstract

To solve the transmission problemof physical layer security(PLS) in relay cognitive radio network (CRN), this paper investigates the PLS transmission scheme of multiple relays CRN, which contains two pairs of secondary nodes without direct link each other.Compared with the model that consists ofa pair of secondary node users and a single relay in terms of theoretical analysis and optimization, the proposed scheme is more complicated.To maximizethe joint secret rate of the secondary users,power allocation of the twosecondarysource transmission node withbeamforming andartificial noise assist (PBNAS) is obtained.Furthermore, exploiting the semidefinite programming theory (SDR) and the successive convex approximation (SCA) method, the original complex nonconvex problem is transformed into a convex optimization problem, and the iterative procedure is summarized.Finally, the security transmission rate versus different number relays andrelays total power is simulated.The simulation results show that the security performance of the PBNAS scheme is the best.

DOI
10.2991/cnct-16.2017.35

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To solve the transmission problemof physical layer security(PLS) in relay cognitive radio network (CRN), this paper investigates the PLS transmission scheme of multiple relays CRN, which contains two pairs of secondary nodes without direct link each other.Compared with the model that consists ofa pair of secondary node users and a single relay in terms of theoretical analysis and optimization, the proposed scheme is more complicated.To maximizethe joint secret rate of the secondary users,power allocation of the twosecondarysource transmission node withbeamforming andartificial noise assist (PBNAS) is obtained.Furthermore, exploiting the semidefinite programming theory (SDR) and the successive convex approximation (SCA) method, the original complex nonconvex problem is transformed into a convex optimization problem, and the iterative procedure is summarized.Finally, the security transmission rate versus different number relays andrelays total power is simulated.The simulation results show that the security performance of the PBNAS scheme is the best.
In an underlay cognitive simultaneous wireless information and power transfer (SWIPT) network, communication from secondary user (SU) to secondary destination (SD) is accomplished with decode-and-forward (DF) relays.Multiple energy-constrained relays are assumed to harvest energy from SU via power splitting (PS) protocol and complete SU secure information transmission with beamforming.Hence, physical layer security (PLS) is investigated in cognitive SWIPT network.In order to interfere with eavesdropper and improve relay's energy efficiency, a destination-assisted jamming scheme is proposed.Namely, SD transmits artificial noise (AN) to interfere with eavesdropping, while jamming signal can also provide harvested energy to relays.Beamforming vector and power splitting ratio are jointly optimized with the objective of SU secrecy capacity maximization.We solve this non-convex optimization problem via a general two-stage procedure.Firstly, we obtain the optimal beamforming vector through semi-definite relaxation (SDR) method with a fixed power splitting ratio.Secondly, the best power splitting ratio can be obtained by one-dimensional search.We provide simulation results to verify the proposed solution.Simulation results show that the scheme achieves the maximum SD secrecy rate with appropriate selection of power splitting ratio, and the proposed scheme guarantees security in cognitive SWIPT networks.
We consider physical-layer security in a novel MISO cooperative overlay cognitive radio network (CRN) with a single eavesdropper. We aim to design an artificial noise (AN) aided secondary transmit strategy to maximize the joint achievable secrecy rate of both primary and secondary links, subject to a global secondary transmit power constraint and guaranteeing any transmission of secondary should at least not degrade the receive quality of primary network, under the assumption that global CSI is available. The resulting optimization problem is challenging to solve due to its non-convexity in general. A computationally efficient approximation methodology is proposed based on the semidefinite relaxation (SDR) technique and followed by a two-step alternating optimization algorithm for obtaining a local optimum for the corresponding SDR problem. This optimization algorithm consists of a one-dimensional line search and a non-convex optimization problem, which, however, through a novel reformulation, can be approximated as a convex semidefinite program (SDP). Analysis on the extension to multiple eavesdroppers scenario is also provided. Simulation results show that the proposed AN-aided joint secrecy rate maximization design (JSRMD) can significantly boost the secrecy performance over JSRMD without AN.
In this paper, we address physical layer security for amplify-and-forward (AF) multi-antenna relay systems in the presence of multiple eavesdroppers. A robust joint design of cooperative beamforming (CB) and artificial noise (AN) is proposed with imperfect channel state information (CSI) of both the destination and the eavesdroppers. We aim to maximize the worst-case secrecy rate subject to the sum power and the per-antenna power constraints at the relay. Such joint design problem is non-convex. By utilizing the semidefinite relaxation (SDR) technique, S-procedure and the successive convex approximation (SCA) algorithm, the original non-convex optimization problem is recast into a series of semidefinite programs (SDPs) which can be efficiently solved using interior-methods. Simulation results are presented to verify the effectiveness of the proposed design.
In this study, the physical layer security for cognitive radio network (CRN) will be investigated in which a secondary user transmitter (SU-Tx) sends confidential information to a SU receiver (SU-Rx) on the same frequency band of a primary user (PU) in the presence of an eavesdropper receiver. Moreover, relay selection scheme is proposed for the security constrained CRNs with single eavesdropper, multiple eavesdroppers and PUs. The proposed scheme selects a trusted decode and forward relay to assist the SU-Tx and maximise the achievable secrecy rate that is subjected to the interference power constraints at the PUs for the different number of eavesdroppers and PUs under available channel knowledge. The SU cooperates with relays only when a high secrecy rate is achieved. Secrecy rate and secrecy outage probability are the two performance metrics that are used to verify the effectiveness of the proposed scheme although asymptotic approximations of the secrecy outage probability are also derived. Simulation and analytical results demonstrate that the performance improvement of the proposed scheme reaches to the double relative to the conventional scheme for the secrecy capacity.
In this paper, we address the physical-layer security issue of a secondary user (SU) in a spectrum-sharing cognitive radio network (CRN) from an information-theoretic perspective. Specially, we consider a secure multiple-input single-output (MISO) cognitive radio channel, where a multi-antenna SU transmitter (SU-Tx) sends confidential information to a legitimate SU receiver (SU-Rx) in the presence of an eavesdropper and on the licensed band of a primary user (PU). The secrecy capacity of the channel is characterized, which is a quasiconvex optimization problem of finding the capacity-achieving transmit covariance matrix under the joint transmit power and interference power constraints. Two numerical approaches are proposed to derive the optimal transmit covariance matrix. The first approach recasts the original quasiconvex problem into a single convex semidefinite program (SDP) by exploring its inherent convexity; while the second one explores the relationship between the secure CRN and the conventional CRN and transforms the original problem into a sequence of optimization problems associated with the conventional CRN, which helps to prove that beamforming is the optimal strategy for the secure MISO CR channel. In addition, to reduce the computational complexity, three suboptimal schemes are presented, namely, scaled secret beamforming (SSB), projected secret beamforming (PSB) and projected cognitive beamforming (PCB). Lastly, computer simulation results show that the three suboptimal schemes can approach the secrecy capacity well under certain conditions.
This paper studies the design of cooperative beamforming (CB) and cooperative jamming (CJ) for the physical layer security of an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. The secrecy rate maximization (SRM) problem of such a network is to maximize the difference of two concave functions, a problem which is non-convex and has no efficient solution. Based on the inner convex approximation (ICA) and semidefinite relaxation (SDR) techniques, we propose two novel low-complexity schemes to design CB and CJ for SRM in the AF network. In the first strategy, relay nodes adopt the CB only to secure transmission. Based on ICA, this design guarantees convergence to a Karush-Kuhn-Tucker (KKT) solution of the SDR of the original problem. In the second strategy, the optimal joint CB and CJ design is studied and the proposed joint design can guarantee convergence to a KKT solution of the original problem. Moreover, in the second strategy, we prove that SDR always has a rank-1 solution for the SRM problem. Simulation results show the superiority of the proposed schemes.