Secure Transmission in Satellite-UAV Integrated System Against Eavesdropping and Jamming:A Two-Level Stackelberg Game Model

Aiming at the physical layer security(PLS)secure transmission existing in the information backhaul link of the satellite-UAV integrated(SUI)network,a two-layer Stackelberg game model(TSGM)that can resist full-duplex(FD)eavesdropping and jamming attacks is proposed.The confrontation relationship between the UAV network and the attacker is established as the first layer Stackelberg game.The source UAV adjusts its own transmission power strategy according to the attacker’s jamming strategy to resist malicious jamming attacks.The internal competition and cooperation relationship in UAV network is modeled as the second layer Stackelberg game,and the optimal cooperative UAV transmits jamming signal to the attacker to resist malicious eavesdropping attacks.Aiming at the“selfishness”of UAV nodes,a price incentive mechanism is established to encourage UAV to actively participate in cooperation,so as to maximize the advantages of cooperative communication.For the proposed TSGM,we construct the utility function and analyze the closed equilibrium solution of the game model,and design a three-stage optimal response iterative(TORI)algorithm to solve the game equilibrium.The simulation results show that the proposed TSGM can effectively increase the utility of the source UAV and improve the enthusiasm of cooperation compared with other power control models.

Secure resource allocation against colluding eavesdropping in a user-centric cell-free massive multiple-input multiple-output system

We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive eavesdroppers.To address the problem of limited pilot resources,a scheme is proposed to allocate the pilot with the minimum pollution to users based on access point selection and optimize the pilot transmission power to improve the accuracy of channel estimation.Aiming at the secure transmission problem under a colluding eavesdropping environment by multiple passive eavesdroppers,based on the local partial zero-forcing precoding scheme,a transmission power optimization scheme is formulated to maximize the system’s minimum security spectral efficiency.Simulation results show that the proposed scheme can effectively reduce channel estimation error and improve system security.

Joint power control and passive beamforming optimization in RIS-assisted anti-jamming communication

Due to the openness of the wireless propagation environment,wireless networks are highly susceptible to malicious jamming,which significantly impacts their legitimate communication performance.This study investigates a reconfigurable intelligent surface(RIS)assisted anti-jamming communication system.Specifically,the objective is to enhance the system’s anti-jamming performance by optimizing the transmitting power of the base station and the passive beamforming of the RIS.Taking into account the dynamic and unpredictable nature of a smart jammer,the problem of joint optimization of transmitting power and RIS reflection coefficients is modeled as a Markov decision process(MDP).To tackle the complex and coupled decision problem,we propose a learning framework based on the double deep Q-network(DDQN)to improve the system achievable rate and energy efficiency.Unlike most power-domain jamming mitigation methods that require information on the jamming power,the proposed DDQN algorithm is better able to adapt to dynamic and unknown environments without relying on the prior information about jamming power.Finally,simulation results demonstrate that the proposed algorithm outperforms multi-armed bandit(MAB)and deep Q-network(DQN)schemes in terms of the anti-jamming performance and energy efficiency.