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: "capacity considerations for secondary networks in tv white space"
  Abstract: The so-called `TV white spaces' (TVWS) - representing unused TV channels in any given location as the result of the transition to digital broadcasting - designated by U.S. Federal Communications Commission (FCC) for unlicensed use presents significant new opportunities within the context of emerging 4G networks for developing new wireless access technologies that meet the goals of the US National Broadband Plan (notably true broadband access for an increasing fraction of the population). There are multiple challenges in realizing this goal; the most fundamental being the fact that the available WS capacity is currently not accurately known, since it depends on a multiplicity of factors - including system parameters of existing incumbents (broadcasters), propagation characteristics of local terrain as well as FCC rules. In this paper, we explore the capacity of white space networks by developing a detailed model that includes all the major variables, and is cognizant of FCC regulations that provide constraints on incumbent protection. Real terrain information and propagation models for the primary broadcaster and adjacent channel interference from TV transmitters are included to estimate their impact on achievable WS capacity. The model is later used to explore various trade-offs between network capacity and system parameters and suggest possible amendments to FCC's incumbent protection rules in the favor of furthering white space capacity.

Connected through hyperedge HE-1 (induced by source paper "sas assisted coexistence aware dynamic channel assignment in cbrs band"):
  with members:
    - "a variant of the maximum weight independent set problem"
    - "approximation algorithms for secondary spectrum auctions"
    - "adaptive channel allocation spectrum etiquette for cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "optimizing city wide wi fi networks in tv white spaces"):
  with members:
    - "channel assignment for throughput maximization in cognitive radio networks"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-3 (induced by source paper "pricing mechanisms for crowd sensed spatial statistics based radio mapping"):
  with members:
    - "crowdsourcing with tullock contests a new perspective"

Connected through hyperedge HE-4 (induced by source paper "spectrum sharing between a surveillance radar and secondary wi fi networks"):
  with members:
    - "simplifying the configuration of 802 11 wireless networks with effective snr"

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.NI(Networking and Internet Architecture)