Legitimate surveillance has attracted more and more concern,and effective proactive intervention can eavesdrop the illegitimate information.In this paper,we propose legitimate eavesdropping over a two-hop suspicious c...Legitimate surveillance has attracted more and more concern,and effective proactive intervention can eavesdrop the illegitimate information.In this paper,we propose legitimate eavesdropping over a two-hop suspicious communication link by two full-duplex legitimate monitors(LMs)based on multi-agent deep deterministic policy gradient(MADDPG)algorithm in two phases.In phase 1,the suspicious transmitter sends information to the suspicious assistant relay,and the assistant relay decodes and forwards the received message to the suspicious receiver in phase 2.Meanwhile,two LMs cooperatively emit jamming to suspicious relay and receiver during each phase.Particularly,each LM is considered to be an energy-limited device,and eavesdropping is a long-term process,so we adopt expected eavesdropping energy efficiency(EEE)over a period of time to evaluate eavesdropping performance.However,for two LMs,how to cooperatively make jamming power decision at each hop in a dynamic environment is a huge challenge.Therefore,MADDPG algorithm,as a multi-agent reinforcement learning approach with the advantage of dynamic decision-making,is utilized to solve the issue of jamming power decision for each LM.In the simulation,the results show that our proposed cooperative jamming scheme can obtain higher expected EEE.展开更多
基金the National Natural Science Foundation of China under Grant 61971190the Fundamental Research Funds for the Central Universities under Grant 2019MS089+2 种基金the Hebei Province Natural Science Foundation under Grant F2016502062 and Grant E2019502039the Beijing Natural Science Foundation under Grant 4164101the Key Project of Science and Technology Research in Higher Education of Hebei Province under Grant ZD2021406。
文摘Legitimate surveillance has attracted more and more concern,and effective proactive intervention can eavesdrop the illegitimate information.In this paper,we propose legitimate eavesdropping over a two-hop suspicious communication link by two full-duplex legitimate monitors(LMs)based on multi-agent deep deterministic policy gradient(MADDPG)algorithm in two phases.In phase 1,the suspicious transmitter sends information to the suspicious assistant relay,and the assistant relay decodes and forwards the received message to the suspicious receiver in phase 2.Meanwhile,two LMs cooperatively emit jamming to suspicious relay and receiver during each phase.Particularly,each LM is considered to be an energy-limited device,and eavesdropping is a long-term process,so we adopt expected eavesdropping energy efficiency(EEE)over a period of time to evaluate eavesdropping performance.However,for two LMs,how to cooperatively make jamming power decision at each hop in a dynamic environment is a huge challenge.Therefore,MADDPG algorithm,as a multi-agent reinforcement learning approach with the advantage of dynamic decision-making,is utilized to solve the issue of jamming power decision for each LM.In the simulation,the results show that our proposed cooperative jamming scheme can obtain higher expected EEE.
