Recently, physical layer security has been recognized as a new design paradigm to provide security in wireless networks. In contrast to the existing conventional cryptographic methods, physical layer security exploits the dynamics of fading channels to enhance security of wireless communications. This paper studies optimization frameworks for a multicasting network in which a transmitter broadcasts the same information to a group of legitimate users in the presence of multiple eavesdroppers. In particular, power minimization and secrecy rate maximization problems are investigated for a multicasting secrecy network. First, the power minimization problem is solved for different numbers of legitimate users and eavesdroppers. Next, the secrecy rate maximization problem is investigated with the help of private jammers to improve the achievable secrecy rates through a game theoretic approach. These jammers charge the transmitter for their jamming services based on the amount of interference caused to the eavesdroppers. For a fixed interference price scenario, a closed-form solution for the optimal interference requirement to maximize the revenue of the transmitter is derived. This rate maximization problem for a nonfixed interference price scenario is formulated as a Stackelberg game in which the jammers and transmitter are the leaders and follower, respectively. For the proposed game, a Stackelberg equilibrium is derived to maximize the revenues of both the transmitter and the private jammers. To support the derived theoretical results, simulation results are provided with different numbers of legitimate users and eavesdroppers. In addition, these results show that physical layer security based jamming schemes could be incorporated in emerging and future wireless networks to enhance the quality of secure communications.
Recently, physical layer security has been recognized as a new design paradigm to provide security in wireless networks. In contrast to the existing conventional cryptographic methods, physical layer security exploits the dynamics of fading channels to enhance security of wireless communications. This paper studies optimization frameworks for a multicasting network in which a transmitter broadcasts the same information to a group of legitimate users in the presence of multiple eavesdroppers. In particular, power minimization and secrecy rate maximization problems are investigated for a multicasting secrecy network. First, the power minimization problem is solved for different numbers of legitimate users and eavesdroppers. Next, the secrecy rate maximization problem is investigated with the help of private jammers to improve the achievable secrecy rates through a game theoretic approach. These jammers charge the transmitter for their jamming services based on the amount of interference caused to the eavesdroppers. For a fixed interference price scenario, a closed-form solution for the optimal interference requirement to maximize the revenue of the transmitter is derived. This rate maximization problem for a nonfixed interference price scenario is formulated as a Stackelberg game in which the jammers and transmitter are the leaders and follower, respectively. For the proposed game, a Stackelberg equilibrium is derived to maximize the revenues of both the transmitter and the private jammers. To support the derived theoretical results, simulation results are provided with different numbers of legitimate users and eavesdroppers. In addition, these results show that physical layer security based jamming schemes could be incorporated in emerging and future wireless networks to enhance the quality of secure communications.
This paper investigates secrecy rate optimization for a multicasting network, in which a transmitter broadcasts the same information to multiple legitimate users in the presence of multiple eavesdroppers. In order to improve the achievable secrecy rates, private jammers are employed to generate interference to confuse the eavesdroppers. These private jammers charge the legitimate transmitter for their jamming services based on the amount of interference received at the eavesdroppers. Therefore, this secrecy rate maximization problem is formulated as a Stackelberg game, in which the private jammers and the transmitter are the leaders and the follower of the game, respectively. A fixed interference price scenario is considered first, in which a closed-form solution is derived for the optimal amount of interference generated by the jammers to maximize the revenue of the legitimate transmitter. Based on this solution, the Stackelberg equilibrium of the proposed game, at which both legitimate transmitter and the private jammers achieve their maximum revenues, is then derived. Simulation results are also provided to validate these theoretical derivations.
This paper investigates secrecy rate optimization for a multicasting network, in which a transmitter broadcasts the same information to multiple legitimate users in the presence of multiple eavesdroppers. In order to improve the achievable secrecy rates, private jammers are employed to generate interference to confuse the eavesdroppers. These private jammers charge the legitimate transmitter for their jamming services based on the amount of interference received at the eavesdroppers. Therefore, this secrecy rate maximization problem is formulated as a Stackelberg game, in which the private jammers and the transmitter are the leaders and the follower of the game, respectively. A fixed interference price scenario is considered first, in which a closed-form solution is derived for the optimal amount of interference generated by the jammers to maximize the revenue of the legitimate transmitter. Based on this solution, the Stackelberg equilibrium of the proposed game, at which both legitimate transmitter and the private jammers achieve their maximum revenues, is then derived. Simulation results are also provided to validate these theoretical derivations.
In this paper, we study different secrecy rate optimization techniques for a multiple-input–multiple-output (MIMO) secrecy channel, where a multiantenna cooperative jammer is employed to improve secret communication in the presence of a multiantenna eavesdropper. Specifically, we consider two optimization problems, namely, power minimization and secrecy rate maximization. These problems are not jointly convex in terms of the transmit covariance matrices of the legitimate transmitter and the cooperative jammer. To circumvent these nonconvexity issues, we alternatively design the transmit covariance matrix of the legitimate transmitter and the cooperative jammer. For a given transmit covariance matrix at the cooperative jammer, we solve the power minimization and secrecy rate maximization problems based on a Taylor series expansion. Then, we propose two iterative algorithms to solve these approximated problems. In addition, we develop a robust scheme by incorporating channel uncertainties associated with the eavesdropper. By exploitingS-Procedure, we show that these robust optimization problems can be formulated into semidefinite programming. Moreover, we consider the secrecy rate maximization problem based on game theory, where the jammer introduces charges for its jamming service based on the amount of the interference caused to the eavesdropper. This secrecy rate maximization problem is formulated into aStackelberggame where the jammer and the transmitter are the leader and the follower of the game, respectively. For the proposed game,Stackelbergequilibrium is analytically derived. Simulation results have been provided to validate the convergence and performance of the proposed algorithms. In addition, it is shown that the proposed robust scheme outperforms the nonrobust scheme in terms of the achieved secrecy rate and the worst-case secrecy rate. Finally, theStackelbergequilibrium solution has been validated through numerical results.
This paper investigates the secrecy rate maximization problem for the multiple-input-single-output multiple-antenna-eavesdropper (MISOME) wiretap channel with multiple randomly located jammers. The multi-antenna base station (BS) transmits information signals along with artificial noise (AN) to disturb the eavesdropper. Moreover, the friendly jammers are properly selected to assist the legitimate link for better secure transmission with some payoffs. With this system model, we first formulate a Stackelberg game between the BS and the assisting jammers with full channel state information. Stackelberg equilibriums, including optimal fraction of transmit power for AN, optimal transmit power, and asking prices of assisting jammers, are first proved to exist and then analytically derived. A policy iterative algorithm is also proposed to obtain the optimal solutions. We then extend the Stackelberg game to the case of MISOME broadcast wiretap channel with channel distribution information of eavesdropper. Numerical results verify the accuracy of the derived results and the efficiency of the proposed algorithm. The results reveal that the proposed jammer-assisted secure transmission can greatly improve the secrecy performance and meanwhile save more energy for information signals, which is significant for future wireless communication.
In this thesis, we study the physical layer security in downlink multi-user wireless networks. Traditionally, security has been addressed by cryptography at the higher layers of the communication stack. Security at the physical layer has been a major research topic in recent years. We study two different precoder designs alongside artificial noise (AN) to mitigate multi-user interference and deteriorate reception at the eavesdropper (Eve). We study the large scale analysis to calculate the secrecy sum-rate for these two cases and analyze the effect of AN on the system. First, we consider the worst case scenario, when eavesdropper's (Eve's) rate is not deteriorated by the interference caused by the legitimate users. Later, we investigate how interference from legitimate users would affect the large scale security sum rate. At the end, we assume more practical situation where the channel state information at the transmitter is not perfect due to feedback limitation and estimation error. We first study block diagonalization (BD) precoding. We derive the asymptotic secrecy sum-rate of BD for physical layer security in downlink multi-user wireless networks using artificial noise (AN). We first derive the secrecy sum-rate assuming that the channel of the eavesdropper is not known at the transmitter and derive the asymptotic secrecy sum-rate. Then we derive the optimum power allocation for asymptotic secrecy sum-rate. We design the system based on large scale analysis for different special cases. Simulation results show that the proposed precoders outperform channel inversion (CI) and regularized channel inversion (RCI) schemes at all SNRs. We also show that as the number of receive antennas of each user increases, the sum-rate gap between the proposed scheme and existing methods increases. We, then, study two methods of regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We compare the complexity analysis of these two methods in terms of floating point operations per second (FLOPS). We derive the secrecy and asymptotic secrecy sum-rates for these schemes. We also derive closed form expressions for the asymptotic optimal power allocation to the AN signal and legitimate users. Simulations show RBD precoding outperform regularized channel inversion (RCI) in terms of secrecy sum-rate with a margin of 0.5 bits/s/Hz. Also, simulation results show our closed-form asymptotic secrecy sum-rates matches closely with the simulations for perfect and imperfect CSIT. We also study the effect of interference on BD precoding scheme. In the first two studies the worst case scenarios was considered and the effect of interference was not considered at the eavesdropper. We first derive the closed-form secrecy and asymptotic secrecy sum-rates for this scheme. Then, we derive the optimum power allocation. Using the derived optimum power allocation, we determine the conditions under which adding AN helps. We also investigate the optimum number of users, number of antennas at the eavesdropper, and the number of transmit antennas to fully study the conditions where using AN improves performance. We show that as the number of users increases or the number of receive antennas at the eavesdropper decreases, improved performance is achieved by allocating a smaller fraction of the total power to transmit the AN. The closed form expressions for the secrecy sum rate (SSR) and optimum power allocation closely match our simulation results. In Chapter 5, we study the effect of imperfect channel state information at the transmitter (CSIT) for each case studied in earlier chapters. We first study the effect of imperfect CSIT for BD precoding in both scenarios when interference does and does not exist at eavesdropper. We show that the imperfect CSI play the same role as interference for the desired users. Then, we study the effect of imperfect CSIT for RBD precoding when interference does not exist at eavesdropper. We show as channel estimation error increases, the secrecy sum-rate decreases. This is due to the fact that channel estimation error just affects the desired users' rate and has no effect on eavesdropper's performance. Finally, in the last chapter, we conclude our thesis and provide some road map for future--Author's abstract