Research On IRS Communication Countermeasure Strategy Under Uncertain Information Condition

With the continuous improvement of electronic warfare theory,the game in electromagnetic field is escalating,and the traditional interference decision-making method can not cope with the new confrontation situation.To solve these problems,cognitive technology and electronic warfare are combined to achieve environmental awareness,online information processing,efficient decision making and rational response.At the same time,with the development of 5G/B5 G communication technology,its characteristics of high speed and low delay will help each combat platform to form the Internet to achieve barrier-free communication,the application of IRS will help millimeter wave communication improve the transmission environment and alleviate the problem of large penetration loss.Therefore,it is of practical significance to study the electronic warfare of millimeter-wave communication of IRS relay in the future battlefield environment.Combined with cognitive electronic warfare and IRS communication,this paper studies the jamming strategy of the jammer by learning channel information(and beam bandwidth)and sensing spectrum,considering two kinds of uncertain settings of information.It introduces the bilevel optimization theory,the duality and robust optimization to provide theoretical support for the research work of this paper.The assumption is made that the jammer is uncertain about the signal power of the full power beam reaching the receiving terminal,and the problem of how to allocate the jammer UAV to minimize the total received signal power of the jammer terminal is studied under the condition of the limited number of UAVs.Then it further assumes that the jammer is uncertain about the exact maximum bandwidth occupied by each beam and studies how to allocate a limited number of jammers to minimize the total power received by the enemy under the condition of dual information uncertainty.The main work of this paper includes the following points: the decision models of the jammer and the Communicator are proposed to describe the communication interference scenarios,the jammer’s decision problem is described as a sequential decision problem,the decision at each stage is modeled as a multi-level programming model,the communication decision of the Communicator is modeled as a linear programming;two learning styles are proposed to learn information about the enemy and ensure that the jammer constantly updates the uncertain set when using greedy and robust jamming strategies to make decision;in the case of uncertainty of the power reaching the terminal of single beam,the multilevel decision model at each stage is transformed into a mixed integer linear programming model by equivalent transformation,it proves the convergence of greedy and robust strategies and the optimality of the final decision and provides the criterion for the jammer to judge whether it has made the optimal decision when it does not have full information about the Communicator;in the case of multiple information uncertainties,robust constraints are used to transform the multilevel decision model of the jammer at each stage into a bilevel programming problem and solve it,the simulation results verify the convergence and global optimality of the interference strategy in this scenario.