human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "channel impulse response based distributed physical layer authentication"
  Abstract: In this preliminary work, we study the problem of {\it distributed} authentication in wireless networks. Specifically, we consider a system where multiple Bob (sensor) nodes listen to a channel and report their {\it correlated} measurements to a Fusion Center (FC) which makes the ultimate authentication decision. For the feature-based authentication at the FC, channel impulse response has been utilized as the device fingerprint. Additionally, the {\it correlated} measurements by the Bob nodes allow us to invoke Compressed sensing to significantly reduce the reporting overhead to the FC. Numerical results show that: i) the detection performance of the FC is superior to that of a single Bob-node, ii) compressed sensing leads to at least $20\%$ overhead reduction on the reporting channel at the expense of a small ($<1$ dB) SNR margin to achieve the same detection performance.

Connected through hyperedge HE-1 (induced by source paper "on the effective capacity of an underwater acoustic channel under impersonation attack"):
  with members:
    - "impersonation detection in line of sight underwater acoustic sensor networks"
    - "physical layer authentication in mission critical mtc networks a security and delay performance analysis"
    - "energy efficiency optimization for mimo ofdm mobile multimedia communication systems with qos constraints"
    - "effective capacity of delay constrained cognitive radio links exploiting primary feedback"
    - "effective capacity of two hop wireless communication systems"
    - "effective capacity analysis of cognitive radio channels for quality of service provisioning"
    - "using the physical layer for wireless authentication in time variant channels"

Connected through hyperedge HE-2 (induced by source paper "physical layer authentication in mission critical mtc networks a security and delay performance analysis"):
  with members:
    - "application of machine learning for channel based message authentication in mission critical machine type communication"
    - "physical layer authentication for mission critical machine type communication using gaussian mixture model based clustering"
    - "secure transmission of delay sensitive data over wireless fading channels"
    - "fingerprints in the ether using the physical layer for wireless authentication"
    - "using the physical layer for wireless authentication in time variant channels"

Question: Please tell me which class the center node 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)