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 "on the optimality of treating interference as noise general message sets"):
  Abstract: In a K-user Gaussian interference channel, it has been shown that if for each user the desired signal strength is no less than the sum of the strengths of the strongest interference from this user and the strongest interference to this user (all values in dB scale), then treating interference as noise (TIN) is optimal from the perspective of generalized degrees-of-freedom (GDoF) and achieves the entire channel capacity region to within a constant gap. In this work, we show that for such TIN-optimal interference channels, even if the message set is expanded to include an independent message from each transmitter to each receiver, operating the new channel as the original interference channel and treating interference as noise is still optimal for the sum capacity up to a constant gap. Furthermore, we extend the result to the sum-GDoF optimality of TIN in the general setting of X channels with arbitrary numbers of transmitters and receivers.

Includes members:
  Member "on the optimality of treating interference as noise":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimality of simple layered superposition coding in the 3 user miso bc with finite precision csit")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "the capacity region of the mimo interference channel and its reciprocity to within a constant gap":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards an extremal network theory robust gdof gain of transmitter cooperation over tin")
  Member "interference alignment from degrees of freedom to constant gap capacity approximations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "a digital interface for gaussian relay and interference networks lifting codes from the discrete superposition model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "compress and forward scheme for relay networks backword decoding and connection to bisubmodular flows")
  Member "capacity regions and sum rate capacities of vector gaussian interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "signal processing and optimal resource allocation for the interference channel")
  Member "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "capacity bounds for the gaussian interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vector gaussian successive refinement with degraded side information")

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)