Transmitter Optimization Techniques for Physical Layer Security

Information security is one of the most critical issues in wireless networks as the signals transmitted through wireless medium are more vulnerable for interception. Although the existing conventional security techniques are proven to be safe, the broadcast nature of wireless communications introduces different challenges in terms of key exchange and distributions. As a result, information theoretic physical layer security has been proposed to complement the conventional security techniques for enhancing security in wireless transmissions. On the other hand, the rapid growth of data rates introduces different challenges on power limited mobile devices in terms of energy requirements. Recently, research work on wireless power transfer claimed that it has been considered as a potential technique to extend the battery lifetime of wireless networks. However, the algorithms developed based on the conventional optimization approaches often require iterative techniques, which poses challenges for real-time processing. To meet the demanding requirements of future ultra-low latency and reliable networks, neural network (NN) based approach can be employed to determine the resource allocations in wireless communications. This thesis developed different transmission strategies for secure transmission in wireless communications. Firstly, transmitter designs are focused in a multiple-input single-output simultaneous wireless information and power transfer system with unknown eavesdroppers. To improve the performance of physical layer security and the harvested energy, artificial noise is incorporated into the network to mask the secret information between the legitimate terminals. Then, different secrecy energy efficiency designs are considered for a MISO underlay cognitive radio network, in the presence of an energy harvesting receiver. In particular, these designs are developed with different channel state information assumptions at the transmitter. Finally, two different power allocation designs are investigated for a cognitive radio network to maximize the secrecy rate of the secondary receiver: conventional convex optimization framework and NN based algorithm

Robust Secrecy Beamforming for MIMO SWIPT with Probabilistic Constraints

This paper considers simultaneous wireless information apower transfer (SWIPT) in a multiple-input multiple-output (MIMO) wiretapnd power transfer (SWIPT) in a multiple-input multiple-output (MIMO) wiretap channel with energy harvesting receivers. The main objective is to keep the probability of the legitimate user's achievable secrecy rate outage as well as the energy receivers' harvested energy outage as caused by CSI uncertainties below given thresholds. This probabilistic-constrained secrecy rate maximization problem presents a significant analytical and computational challenge since any closed-form for the probabilistic constraints with log-det functions is intractable. In this paper, we address this challenging issue using codeviation inequalitiesnvex restrictions. In particular, we derive decomposition-based large deviation inequalities to transform the probabilistic constraints into second-order cone (SOC) constraints which are easier to handle. Then we show that a robust safe solution can be obtained through solving two convex sub-problems in an alternating fashion

Probabilistically Robust SWIPT for Secrecy MISOME Systems

This paper considers simultaneous wireless information and power transfer (SWIPT) in a multiple-input single-output (MISO) downlink system consisting of one multi-antenna transmitter, one single-antenna information receiver (IR), multiple multi-antenna eavesdroppers (Eves) and multiple single-antenna energy-harvesting receivers (ERs). The main objective is to keep the probability of the legitimate user's achievable secrecy rate outage as well as the ERs' harvested energy outage caused by channel state information (CSI) uncertainties below some prescribed thresholds. As is well known, the secrecy rate outage constraints present a significant analytical and computational challenge. Incorporating the energy harvesting (EH) outage constraints only intensifies that challenge. In this paper, we address this challenging issue using convex restriction approaches which are then proved to yield rank-one optimal beamforming solutions. Numerical results reveal the effectiveness of the proposed schemes.Comment: This is an open access article accepted for publication as a regular paper in the IEEE Transactions on Information Forensics & Security. Copyright (c) 2016 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to [email protected]

Transmit optimization techniques for physical layer security

PhD ThesisOver the last several decades, reliable communication has received considerable attention in the area of dynamic network con gurations and distributed processing techniques. Traditional secure communications mainly considered transmission cryptography, which has been developed in the network layer. However, the nature of wireless transmission introduces various challenges of key distribution and management in establishing secure communication links. Physical layer security has been recently recognized as a promising new design paradigm to provide security in wireless networks in addition to existing conventional cryptographic methods, where the physical layer dynamics of fading channels are exploited to establish secure wireless links. On the other hand, with the ever-increasing demand of wireless access users, multi-antenna transmission has been considered as one of e ective approaches to improve the capacity of wireless networks. Multi-antenna transmission applied in physical layer security has extracted more and more attentions by exploiting additional degrees of freedom and diversity gains. In this thesis, di erent multi-antenna transmit optimization techniques are developed for physical layer secure transmission. The secrecy rate optimization problems (i.e., power minimization and secrecy rate maximization) are formulated to guarantee the optimal power allocation. First, transmit optimization for multiple-input single-output (MISO) secrecy channels are developed to design secure transmit beamformer that minimize the transmit power to achieve a target secrecy rate. Besides, the associated robust scheme with the secrecy rate outage probability constraint are presented with statistical channel uncertainty, where the outage probability constraint requires that the achieved secrecy rate exceeds certain thresholds with a speci c probability. Second, multiantenna cooperative jammer (CJ) is presented to provide jamming services that introduces extra interference to assist a multiple-input multipleoutput (MIMO) secure transmission. Transmit optimization for this CJaided MIMO secrecy channel is designed to achieve an optimal power allocation. Moreover, secure transmission is achieved when the CJ introduces charges for its jamming service based on the amount of the interference caused to the eavesdropper, where the Stackelberg game is proposed to handle, and the Stackelberg equilibrium is analytically derived. Finally, transmit optimization for MISO secure simultaneous wireless information and power transfer (SWIPT) is investigated, where secure transmit beamformer is designed with/without the help of arti - cial noise (AN) to maximize the achieved secrecy rate such that satisfy the transmit power budget and the energy harvesting (EH) constraint. The performance of all proposed schemes are validated by MATLAB simulation results

Beamforming and Power Splitting Designs for AN-aided Secure Multi-user MIMO SWIPT Systems

In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output (MIMO) secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem, on the other hand, is shown to be a single- variable optimization that can be solved by one-dimensional (1- D) line search. To reduce computational complexity, a sequential parametric convex approximation (SPCA) method is proposed to find a near-optimal solution. The work is then extended to the imperfect channel state information case with norm-bounded channel errors. Furthermore, tightness of the relaxation for the proposed schemes are validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D but with much lower complexity.Comment: 12 pages, 6 figures, submitted for possible publicatio

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