Observation and research of deep underground multi-physical fields—Huainan–848 m deep experiment

Compared with the surface,the deep environment has the advantages of allowing“super-quiet and ultra-clean”-geophysical field observation with low vibration noise and little electromagnetic interference,which are conducive to the realization of long-term and high-precision observation of multi-physical fields,thus enabling the solution of a series of geoscience problems.In the Panyidong Coal Mine,where there are extensive underground tunnels at the depth of 848 m below sea level,we carried out the first deep-underground geophysical observations,including radioactivity,gravity,magnetic,magnetotelluric,background vibration and six-component seismic observations.We concluded from these measurements that(1)the background of deep subsurface gravity noise in the long-period frequency band less than 2 Hz is nearly two orders of magnitude weaker than that in the surface observation environment;(2)the underground electric field is obviously weaker than the surface electric field,and the relatively high frequency of the underground field,greater than 1 Hz,is more than two orders of magnitude weaker than that of the surface electric field;the east-west magnetic field underground is approximately the same as that at the surface;the relatively high-frequency north-south magnetic field underground,below 10 Hz,is at least one order of magnitude lower than that at the surface,showing that the underground has a clean electromagnetic environment;(3)in addition to the highfrequency and single-frequency noises introduced by underground human activities,the deep underground space has a significantly lower background vibration noise than the surface,which is very beneficial to the detection of weak earthquake and gravity signals;and(4)the underground roadway support system built with ferromagnetic material interferes the geomagnetic field.We also found that for deep observation in the“ultra-quiet and ultra-clean”environment,the existing geophysical equipment and observation technology have problems of poor adaptability and insufficient precision as well as data cleaning problems,such as the effective separation of the signal and noise of deep observation data.It is also urgent to interpret and comprehensively utilize these high-precision multi-physics observation data.

Cooperative Proactive Eavesdropping over Two-Hop Suspicious Communication Based on Reinforcement Learning

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.