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 "feedback capacity of the gaussian interference channel to within 2 bits"):
  Abstract: We characterize the capacity region to within 2 bits/s/Hz and the symmetric capacity to within 1 bit/s/Hz for the two-user Gaussian interference channel (IC) with feedback. We develop achievable schemes and derive a new outer bound to arrive at this conclusion. One consequence of the result is that feedback provides multiplicative gain, i.e., the gain becomes arbitrarily large for certain channel parameters. It is a surprising result because feedback has been so far known to provide no gain in memoryless point-to-point channels and only bounded additive gain in multiple access channels. The gain comes from using feedback to maximize resource utilization, thereby enabling more efficient resource sharing between the interfering users. The result makes use of a deterministic model to provide insights into the Gaussian channel. This deterministic model is a special case of El Gamal-Costa deterministic model and as a side-generalization, we establish the exact feedback capacity region of this general class of deterministic ICs.

Includes members:
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "dependence balance based outer bounds for gaussian networks with cooperation and feedback":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint state sensing and communication over memoryless multiple access channels")
  Member "interference channels with source cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gdof of interference channel with limited cooperation under finite precision csit")
  Member "interference channels with destination cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gdof of interference channel with limited cooperation under finite precision csit")
  Member "completely stale transmitter channel state information is still very useful":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "achievable dof regions of three user mimo broadcast channel with delayed csit")
  Member "feedback capacity of the gaussian interference channel to within 1 7075 bits the symmetric case":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards an extremal network theory robust gdof gain of transmitter cooperation over tin")
  Member "the two user gaussian interference channel a deterministic view":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dof region of the decentralized mimo broadcast channel unicode x2014 how many informed antennas do we need")
  Member "a deterministic approach to wireless relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the deterministic sum capacity of the multiple access wiretap channel")

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)