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 "network coherence time matters aligned image sets and the degrees of freedom of interference networks with finite precision csit and perfect csir"):
  Abstract: This work obtains the first bound that is provably sensitive to network coherence time, i.e., coherence time in an interference network where all channels experience the same coherence patterns. This is accomplished by a novel adaptation of the aligned image sets bound, and settles various open problems noted previously by Naderi and Avestimehr and by Gou et al. For example, a necessary and sufficient condition is obtained for the optimality of 1/2 DoF per user in a partially connected interference network where the channel state information at the receivers (CSIR) is perfect, the channel state information at the transmitters (CSIT) is instantaneous but limited to finite precision, and the network coherence time is T_c= 1. The surprising insight that emerges is that even with perfect CSIR and instantaneous finite precision CSIT, network coherence time matters, i.e., it has a DoF impact.

Includes members:
  Member "sum set inequalities from aligned image sets instruments for robust gdof bounds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dof region of the decentralized mimo broadcast channel unicode x2014 how many informed antennas do we need")
  Member "topological interference management through index coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the separability of parallel miso broadcast channels under partial csit a degrees of freedom region perspective")
  Member "interference networks with no csit impact of topology":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "topological interference management with transmitter cooperation")
  Member "elements of cellular blind interference alignment aligned frequency reuse wireless index coding and interference diversity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "interference management in heterogeneous networks with blind transmitters")
  Member "on the capacity of fading mimo broadcast channels with imperfect transmitter side information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the separability of parallel miso broadcast channels under partial csit a degrees of freedom region perspective")

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)