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 multi cell uplink downlink duality with treating inter cell interference as noise"):
  Abstract: We consider the information-theoretic optimality of treating inter-cell interference as noise in downlink cellular networks modeled as Gaussian interfering broadcast channels. Establishing a new uplink-downlink duality, we cast the problem in Gaussian interfering broadcast channels to that in Gaussian interfering multiple access channels, and characterize an achievable GDoF region under power control and treating inter-cell interference as (Gaussian) noise. We then identify conditions under which this achievable GDoF region is optimal.

Includes members:
  Member "on the optimality of treating inter cell interference as noise in uplink cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimality of treating inter cell interference as noise under finite precision csit")
  Member "opportunistic treating interference as noise":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimality of treating inter cell interference as noise under finite precision csit")
  Member "optimality of treating interference as noise a combinatorial perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimality of treating inter cell interference as noise under finite precision csit")
  Member "on the optimality of treating interference as noise compound interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards an extremal network theory robust gdof gain of transmitter cooperation over tin")
  Member "on the optimality of treating interference as noise general message sets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards an extremal network theory robust gdof gain of transmitter cooperation over tin")
  Member "on the optimality of treating interference as noise for k user parallel gaussian interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the separability of parallel miso broadcast channels under partial csit a degrees of freedom region perspective")
  Member "downlink interference alignment":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimality of treating inter cell interference as noise under finite precision csit")

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)