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 "will the area spectral efficiency monotonically grow as small cells go dense"):
  Abstract: In this paper, we introduce a sophisticated path loss model into the stochastic geometry analysis incorporating both line-of-sight (LoS) and non- line-of-sight (NLoS) transmissions to study their performance impact in small cell networks (SCNs). Analytical results are obtained on the coverage probability and the area spectral efficiency (ASE) assuming both a general path loss model and a special case of path loss model recommended by the 3rd Generation Partnership Project (3GPP) standards. The performance impact of LoS and NLoS transmissions in SCNs in terms of the coverage probability and the ASE is shown to be significant both quantitatively and qualitatively, compared with previous work that does not differentiate LoS and NLoS transmissions. From the investigated set of parameters, our analysis demonstrates that when the density of small cells is larger than a threshold, the network coverage probability will decrease as small cells become denser, which in turn makes the ASE suffer from a slow growth or even a notable decrease. For practical regime of small cell density, the performance results derived from our analysis are distinctively different from previous results, and shed new insights on the design and deployment of future dense/ultra-dense SCNs. It is of significant interest to further study the generality of our conclusion in other network models and with other parameter sets.

Includes members:
  Member "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "downlink cellular network analysis with multi slope path loss models":
    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 "coverage and rate analysis for millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "offloading in heterogeneous networks modeling analysis and design insights":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "modeling and analysis of k tier downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "a tractable approach to coverage and rate in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna 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)