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 information theoretic scaling laws for wireless networks"
  Abstract: With the analysis of the hierarchical scheme, the potential influence of the pre-constant in deriving scaling laws is exposed. It is found that a modified hierarchical scheme can achieve a throughput arbitrarily times higher than the original one, although it is still diminishingly small compared to the linear scaling. The study demonstrates the essential importance of the throughput formula itself, rather than the scaling laws consequently derived.

Connected through hyperedge HE-1 (induced by source paper "on the performance of optimized dense device to device wireless networks"):
  with members:
    - "on the optimality of treating interference as noise"
    - "improved capacity approximations for gaussian relay networks"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "compute and forward strategies for cooperative distributed antenna systems"
    - "capacity scaling of wireless ad hoc networks shannon meets maxwell"
    - "capacity of a class of symmetric simo gaussian interference channels within o 1"
    - "compute and forward harnessing interference through structured codes"
    - "generalized degrees of freedom of the symmetric gaussian k user interference channel"

Connected through hyperedge HE-2 (induced by source paper "improved capacity scaling in wireless networks with infrastructure"):
  with members:
    - "parallel opportunistic routing in wireless networks"
    - "the balanced unicast and multicast capacity regions of large wireless networks"
    - "on capacity scaling in arbitrary wireless networks"
    - "information theoretic operating regimes of large wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-3 (induced by source paper "fundamentals of large sensor networks connectivity capacity clocks and computation"):
  with members:
    - "optimal strategies for computing symmetric boolean functions in collocated networks"
    - "information theoretic bounds for multiround function computation in collocated networks"
    - "distributed source coding for interactive function computation"
    - "lattices for distributed source coding jointly gaussian sources and reconstruction of a linear function"
    - "a deterministic approach to wireless relay networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-4 (induced by source paper "interference alignment in dense wireless networks"):
  with members:
    - "the ergodic capacity of phase fading interference networks"
    - "interference alignment based sum capacity bounds for random dense gaussian interference networks"
    - "the balanced unicast and multicast capacity regions of large wireless networks"
    - "on capacity scaling in arbitrary wireless networks"
    - "ergodic interference alignment"
    - "approaching the capacity of wireless networks through distributed interference alignment"
    - "product multicommodity flow in wireless networks"
    - "information theoretic operating regimes of large wireless networks"

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)