human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "secret key generation based on aoa estimation for low snr conditions"):
  Abstract: In the context of physical layer security, a physical layer characteristic is used as a common source of randomness to generate the secret key. Therefore an accurate estimation of this characteristic is the core for reliable secret key generation. Estimation of almost all the existing physical layer characteristic suffer dramatically at low signal to noise (SNR) levels. In this paper, we propose a novel secret key generation algorithm that is based on the estimated angle of arrival (AoA) between the two legitimate nodes. Our algorithm has an outstanding performance at very low SNR levels. Our algorithm can exploit either the Azimuth AoA to generate the secret key or both the Azimuth and Elevation angles to generate the secret key. Exploiting a second common source of randomness adds an extra degree of freedom to the performance of our algorithm. We compare the performance of our algorithm to the algorithm that uses the most commonly used characteristics of the physical layer which are channel amplitude and phase. We show that our algorithm has a very low bit mismatch rate (BMR) at very low SNR when both channel amplitude and phase based algorithm fail to achieve an acceptable BMR.

Includes members:
  Member "a simple aoa estimation scheme":
    also connected through other hyperedges:
      (none)
  Member "cooperative secret key generation from phase estimation in narrowband fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "design and implementation of secret key agreement for platoon based vehicular cyber physical systems")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)