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: "wireless ad hoc networks strategies and scaling laws for the fixed snr regime"
  Abstract: This paper deals with throughput scaling laws for random ad hoc wireless networks in a rich scattering environment. We develop schemes to optimize the ratio lambda(n) of achievable network sum capacity to the sum of the point-to-point capacities of source-destinations (S-D) pairs operating in isolation. Our focus in this paper is on fixed signal-to-noise ratio (SNR) networks, i.e., networks where the worst case SNR over the S-D pairs is fixed independent of n. For such fixed SNR networks, which include fixed area networks as a special case, we show that collaborative strategies yield a scaling law of lambda(n)=Omega(1/n1/3) in contrast to multihop strategies which yield a scaling law of lambda(n)=Theta(1/radicn). While networks where worst case SNR goes to zero do not preclude the possibility of collaboration, multihop strategies achieve optimal throughput. The plausible reason is that the gains due to collaboration cannot offset the effect of vanishing receive SNR. This suggests that for fixed SNR networks, a network designer should look for network protocols that exploit collaboration

Connected through hyperedge HE-1 (induced by source paper "channel assignment in dense mc mr wireless networks scaling laws and algorithms"):
  with members:
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-2 (induced by source paper "capacity of multiple unicast in wireless networks a polymatroidal approach"):
  with members:
    - "real interference alignment exploiting the potential of single antenna systems"
    - "multiuser broadcast erasure channel with feedback capacity and algorithms"
    - "degrees of freedom of interference channels with comp transmission and reception"
    - "multicommodity flows and cuts in polymatroidal networks"
    - "wireless network information flow a deterministic approach"
    - "computation alignment capacity approximation without noise accumulation"
    - "the degrees of freedom of the 2 hop 2 user interference channel with feedback"
    - "a digital interface for gaussian relay and interference networks lifting codes from the discrete superposition model"

Connected through hyperedge HE-3 (induced by source paper "the balanced unicast and multicast capacity regions of large wireless networks"):
  with members:
    - "on capacity scaling in arbitrary wireless networks"
    - "product multicommodity flow in wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-4 (induced by source paper "linear capacity scaling in wireless networks beyond physical limits"):
  with members:
    - "information theoretic operating regimes of large wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-5 (induced by source paper "an energy based comparison of long hop and short hop routing in mimo networks"):
  with members:
    - "product multicommodity flow in wireless networks"

Connected through hyperedge HE-6 (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"

Connected through hyperedge HE-7 (induced by source paper "throughput scaling of wireless networks with random connections"):
  with members:
    - "opportunistic relaying in wireless networks"
    - "information theoretic operating regimes of large wireless networks"
    - "throughput scaling laws for wireless networks with fading channels"
    - "crystallization in large wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-8 (induced by source paper "a new scaling law on throughput and delay performance of wireless mobile relay networks over parallel fading channels"):
  with members:
    - "rate regions for relay broadcast channels"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc 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)