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 "guaranteeing positive secrecy capacity with finite rate feedback using artificial noise"):
  Abstract: While the impact of finite-rate feedback on the capacity of fading channels has been extensively studied in the literature, not much attention has been paid to this problem under secrecy constraint. In this work, we study the ergodic secret capacity of a multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) wiretap channel with quantized channel state information (CSI) at the transmitter and perfect CSI at the legitimate receiver, under the assumption that only the statistics of eavesdropper CSI is known at the transmitter. We refine the analysis of the random vector quantization (RVQ) based artificial noise (AN) scheme in [1], where a heuristic upper bound on the secrecy rate loss, when compared to the perfect CSI case, was given. We propose a lower bound on the ergodic secrecy capacity. We show that the lower bound and the secrecy capacity with perfect CSI coincide asymptotically as the number of feedback bits and the AN power go to infinity. For practical applications, we propose a very efficient quantization codebook construction method for the two transmit antennas case.

Includes members:
  Member "artificial noise revisited":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "artificial noisy mimo systems under correlated scattering rayleigh fading a physical layer security approach")
  Member "capacity of a multiple antenna fading channel with a quantized precoding matrix":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on optimizing feedback interval for temporally correlated mimo channels with transmit beamforming and finite rate feedback")
  Member "limited feedback based block diagonalization for the mimo broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mimo amplify and forward precoding for networked control systems")
  Member "the secrecy capacity of the mimo wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "quantization bounds on grassmann manifolds and applications to mimo communications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "high dimensional stochastic gradient quantization for communication efficient edge learning")

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)