human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "on the capacity of multi hop wireless networks with partial network knowledge"
  Abstract: In large wireless networks, acquiring full network state information is typically infeasible. Hence, nodes need to flow the information and manage the interference based on partial information about the network. In this paper, we consider multi-hop wireless networks and assume that each source only knows the channel gains that are on the routes from itself to other destinations in the network. We develop several distributed strategies to manage the interference among the users and prove their optimality in maximizing the achievable normalized sum-rate for some classes of networks.

Connected through hyperedge HE-1 (induced by source paper "leveraging physical layer capabilites distributed scheduling in interference networks with local views"):
  with members:
    - "topological interference management through index coding"
    - "sum capacity of interference channels with a local view impact of distributed decisions"
    - "on achieving local view capacity via maximal independent graph scheduling"
    - "q csma queue length based csma ca algorithms for achieving maximum throughput and low delay in wireless networks"
    - "local multicoloring algorithms computing a nearly optimal tdma schedule in constant time"
    - "distributed link scheduling with constant overhead"

Connected through hyperedge HE-2 (induced by source paper "communication through collisions opportunistic utilization of past receptions"):
  with members:
    - "capacity results for binary fading interference channels with delayed csit"
    - "on the degrees of freedom of k user siso interference and x channels with delayed csit"
    - "chernoff hoeffding inequality and applications"
    - "on achieving local view capacity via maximal independent graph scheduling"
    - "completely stale transmitter channel state information is still very useful"
    - "retrospective interference alignment"

Connected through hyperedge HE-3 (induced by source paper "layered interference networks with delayed csi dof scaling with distributed transmitters"):
  with members:
    - "interference and x networks with noisy cooperation and feedback"
    - "capacity results for binary fading interference channels with delayed csit"
    - "ergodic interference alignment with delayed feedback"
    - "on the degrees of freedom of k user siso interference and x channels with delayed csit"
    - "linear degrees of freedom of the mimo x channel with delayed csit"
    - "degrees of freedom of two hop wireless networks everyone gets the entire cake"
    - "fundamental limits of cooperation"
    - "on achieving local view capacity via maximal independent graph scheduling"

Connected through hyperedge HE-4 (induced by source paper "wireless network coding with local network views coded layer scheduling"):
  with members:
    - "sum capacity of interference channels with a local view impact of distributed decisions"
    - "wireless network information flow a deterministic approach"
    - "on achieving local view capacity via maximal independent graph scheduling"
    - "interference alignment for the mimo interference channel with delayed local csit"
    - "completely stale transmitter channel state information is still very useful"
    - "retrospective interference alignment"
    - "exploiting channel correlations simple interference alignment schemes with no csit"
    - "interference alignment with analog channel state feedback"

Question: Please tell me which class the center node 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)