In the Multi-downlink network,the interference among nonorthogonal channels and the malicious interference makes destination nodes not meet the demand of Quality of Service(QoS).So a security transmission method based on zero-sum game model is proposed to solve this physical layer security problem.Utility function based on secrecy rate is built,and the downlink beamforming and power allocation are optimized jointly based on uplink downlink duality to minimize the transmission power and to meet the QoS.The mixed strategy equilibrium and the corresponding secrecy rate can be obtained.Simulation results show that this method can achieve a good secrecy rate.
In the Multi-downlink network,the interference among nonorthogonal channels and the malicious interference makes destination nodes not meet the demand of Quality of Service(QoS).So a security transmission method based on zero-sum game model is proposed to solve this physical layer security problem.Utility function based on secrecy rate is built,and the downlink beamforming and power allocation are optimized jointly based on uplink downlink duality to minimize the transmission power and to meet the QoS.The mixed strategy equilibrium and the corresponding secrecy rate can be obtained.Simulation results show that this method can achieve a good secrecy rate.
The most of existing physical layer security research focus on the situation where decentralized nodes transmit signals to the Base Station(BS).But considering a scenario where nonorthogonal transmission is allowed, when the BS transmits signals to decentralized nodes, the multi-downlinks will interfere each other, decreasing the signal-to-interference-plus-noise ratios (SINRs) at receivers.Focusing on the above problem, this paper optimizes the downlink beamforming and power allocation jointly to meet the SINRs requirement.On this basis, when confronted with synergistic eavesdroping where a malicious jammer helps the eavesdropper to eavesdrop, the BS transmits the artificial noise(AN) to improve the secrecy rate.Then zero-sum game model is proposed to obtain the strategies and corresponding expectation value of the secrecy rate when system reaches the mixed strategy equilibrium.By simulation, this method will obtain a good secrecy rate.
In this letter, we consider a multi-antenna downlink network where a secure user (SU) coexists with a passive eavesdropper. There are two design requirements for such a network. First, the information should be transferred in a secret and efficient manner. Second, the quality of service (QoS), i.e. delay sensitivity, should be take into consideration to satisfy the demands of real-time wireless services. In order to fulfill the two requirements, we combine the physical layer security technique based on switched beam beamforming with an energy-efficient power allocation. The problem is formulated as the maximization of the secrecy energy efficiency subject to delay and power constraints. By solving the optimization problem, we derive an energy-efficient power allocation scheme. Numerical results validate the effectiveness of the proposed scheme.
Non-orthogonal multiple access technology (NOMA), as a potentially promising technology in the 5G/B5G era, suffers from ubiquitous security threats due to the broadcast nature of the wireless medium. In this paper, we focus on artificial-signal-assisted and relay-assisted secure downlink transmission schemes against external eavesdropping in the context of physical layer security, respectively. To characterize the non-cooperative confrontation around the secrecy rate between the legitimate communication party and the eavesdropper, their interactions are modeled as a two-person zero-sum game. The existence of the Nash equilibrium of the proposed game models is proved, and the pure strategy Nash equilibrium and mixed-strategy Nash equilibrium profiles in the two schemes are solved and analyzed, respectively. The numerical simulations are conducted to validate the analytical results, and show that the two schemes improve the secrecy rate and further enhance the physical layer security performance of NOMA systems.
This paper proposes a secure users-oriented multiple-input and single-output non-orthogonal multiple access downlink transmission scheme, where multiple legitimate users are categorized as quality of service (QoS)-required users (QU) and the security-required users (SU) overheard by a passive eavesdropper. The basic idea is to exploit zero-forcing beamforming to cancel interference among SUs, and then several QUs are efficiently scheduled based on the obtained beamforming vectors to divide the legitimate users into several user clusters, in such a way that the QUs could share the concurrent transmissions and help to interfere with the eavesdropper to enhance SU secrecy. The goal is to maximize the achievable minimum secrecy rate and sum secrecy rate of all SUs, respectively, subject to the secrecy outage probability constraint of each SU and the QoS constraint of each QU. To provide a comprehensive investigation, we consider two extreme cases that the eavesdropper has perfect multiuser detection ability (lower bound of secrecy) or does not have multiuser detection ability (upper bound of secrecy). In the lower bound case, the Dinkelbach algorithm and the monotonic optimization-based outer polyblock approximation algorithm are proposed to solve the max-min secrecy rate and max-sum secrecy rate problems, respectively. As for the upper bound case, an alternative optimization-based algorithm is proposed to solve the two non-convex problems. Finally, the superiority of the proposed cases to the conventional orthogonal multiple access one is verified by numerical results.
In this paper, we consider a joint beamforming and jamming design to enhance physical layer security against potential multiple eavesdroppers in a multiple-input and single-output cellular broadcast channel. With perfect channel state information at the base station, we propose various design approaches to improve the secrecy of the target user. Among the proposed approaches, the combined beamforming of maximum ratio transmission and zero-forcing transmission with a combination of maximum ratio jamming and zero-forcing jamming ( with ) shows the best security performance because it utilizes the full transmit antenna dimensions for beamforming and jamming with an efficient power allocation. The simulation results show that the secrecy rate of this particular proposed approach is better than the rates of the considered conventional approaches with quality-of-service and outage probability constraints.
The physical layer security technology is a technical scheme developed in recent years to solve the problem of information security transmission in wireless communication networks. As one of the physical layer security technologies, cooperative jamming often requires collaborative nodes to actively cooperate with other nodes with secure communication requirements to transmit information. In the environment of heterogeneous wireless network, each wireless node is relatively independent, the relationship is both cooperative and competitive, and the nodes are selfish. In this paper, we study the information transmission between the source and destination nodes, and form a virtual beamforming through the cooperation of the jamming nodes to point to the malicious wiretap nodes, so as to achieve the physical layer secure communication. First, the interest distribution relationship between the source node and other cooperative interference nodes is modeled as the Stackelberg game. The source node pays the consumption of the power consumed by the cooperative jamming nodes and motivates the cooperative interference nodes to participate actively. Then, the competition relationship among all the cooperative nodes is built as a non-cooperative game, so as to promote the reasonable pricing of the consumed power when each node participates in collaboration. When the security rate between the source node and destination node is constant, the power allocation of source and cooperative nodes and the equilibrium point of power price exist and are unique. Through the combined optimization of the two games, the power pricing and power allocation can be dynamically optimized according to the change of the network environment. The simulation results show that the power dynamic allocation and power dynamic pricing have good convergence, and the source node provides a train of thought for the selection of cooperative nodes and their number.