Protecting multi-function wireless systems from jammers with backscatter assistance: an intelligent strategy

In this paper, we present a novel unified framework to protect multi-function wireless systems from jamming attacks. Examples of such multi-function system include joint radar and communication (JRC) systems and simultaneous wireless information and power transfer (SWIPT) systems. By abstracting the system functionalities as a joint optimization problem of multiple queues, we achieve effective resistance against jammers for the multi-functions simultaneously.We incorporate different antijamming techniques into one framework. Deception mechanism is adopted to lure the jammer to attack and make its actions more predictable, and ambient backscatter technology is used to leverage the jamming signals. Since conventional Markov decision process (MDP) has only one decision epoch at every time slot, it cannot be used to model the deception strategy which needs two decision epochs to leverage the jamming signals. We therefore formulate the problem using an advanced two-step MDP. After that, a deep reinforcement learning algorithm with a prioritized double deep Q-Learning architecture is proposed to learn optimal strategies in different system states. We show that by jointly considering the multi-functions of the system with potential jamming attacks during design phase, significant improvement can be achieved for both of the system functionalities.Ministry of Education (MOE)National Research Foundation (NRF)This work was supported in part by Alibaba Group through Alibaba Innovative Research (AIR) Program and Alibaba-NTU Singapore Joint Research Institute (JRI), in part by the National Research Foundation, Singapore under the AI Singapore Programme (AISG) (AISG2-RP-2020-019), WASP/NTU Grant M4082187 (4080) and Singapore Ministry of Education (MOE) Tier 1 (RG16/20), in part by the Singapore International Graduate Award (SINGA) scholarship, the Australian Research Council (Discovery Early Career Researcher) under Award DE210100651, in part by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIT) under Grant 2021R1A2C2007638 and in part by ARC under Grants DP190101988 and DP210103410