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 "a brief history on the theoretical analysis of dense small cell wireless networks"):
  Abstract: This article provides dives into the fundamentals of dense and ultra-dense small cell wireless networks, discussing the reasons why dense and ultra-dense small cell networks are fundamentally different from sparse ones, and why the well-known linear scaling law of capacity with the base station (BS) density in the latter does not apply to the former. In more detail, we review the impact of the following factors on ultradense networks (UDNs), (i) closed-access operations and line-of-sight conditions, (ii) the near-field effect, (iii) the antenna height difference between small cell BSs and user equipments (UEs), and (iv) the surplus of idle-mode-enabled small cell BSs with respect to UEs. Combining all these network characteristics and features, we present a more realistic capacity scaling law for UDNs, which indicates (i) the existence of an optimum BS density to maximise the area spectral efficiency (ASE) for a given finite UE density, and (ii) the existence of an optimum density of UEs that can be simultaneously scheduled across the network to maximise the ASE for a given finite BS density.

Includes members:
  Member "optimal base station antenna downtilt in downlink cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a 3d beamforming scheme based on the spatial distribution of user locations")
  Member "sinr and throughput of dense cellular networks with stretched exponential path loss":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "ultra dense networks is there a limit to spatial spectrum reuse":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal base station antenna downtilt in downlink cellular networks")
  Member "wireless powered dense cellular networks how many small cells do we need":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "covert transmission with a self sustained relay")
  Member "inter operator base station coordination in spectrum shared millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "modeling co location in multi operator mmwave networks with spectrum sharing")
  Member "downlink cellular network analysis with los nlos propagation and elevated base stations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "modeling and performance analysis in cache enabled millimeter wave hetnets with access and backhaul integration")
  Member "performance impact of base station antenna heights in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "modeling infrastructure sharing in mmwave networks with shared spectrum licenses":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks")

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.NI(Networking and Internet Architecture)