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 through overhearing"):
  Abstract: In this paper we examine the value of feedback that comes from overhearing, without dedicated feedback resources. We focus on a simple model for this purpose: a deterministic two-hop interference channel, where feedback comes from overhearing the forward-links. A new aspect brought by this setup is the dual-role of the relay signal. While the relay signal needs to convey the source message to its corresponding destination, it can also provide a feedback signal which can potentially increase the capacity of the first hop. We derive inner and outer bounds on the sum capacity which match for a large range of the parameter values. Our results identify the parameter ranges where overhearing can provide non-negative capacity gain and can even achieve the performance with dedicated-feedback resources. The results also provide insights into which transmissions are most useful to overhear.

Includes members:
  Member "perfect output feedback in the two user decentralized interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "strategic communication with side information at the decoder")
  Member "two way interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "two way function computation")
  Member "on constant gaps for the two way gaussian interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "degrees of freedom of the mimo three way channel with node intermittency")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "interference channels with rate limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "capacity results for intermittent x channels with delayed channel state feedback")
  Member "feedback capacity of the gaussian interference channel to within 2 bits":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity limits of full duplex cellular network")
  Member "on channel output feedback in deterministic interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "two way interference channel capacity how to have the cake and eat it too")

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)