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 "performance impact of los and nlos transmissions in dense cellular networks"):
  Abstract: In this paper, we introduce a sophisticated path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions to study their impact on the performance of dense small cell networks (SCNs). Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE), assuming both a general path loss model and a special case with a linear LoS probability function. The performance impact of LoS and NLoS transmissions in dense SCNs in terms of the coverage probability and the ASE is significant, both quantitatively and qualitatively, compared with the previous work that does not differentiate LoS and NLoS transmissions. Our analysis demonstrates that the network coverage probability first increases with the increase of the base station (BS) density, and then decreases as the SCN becomes denser. This decrease further makes the ASE suffer from a slow growth or even a decrease with network densification. The ASE will grow almost linearly as the BS density goes ultra dense. For practical regime of the BS density, the performance results derived from our analysis are distinctively different from previous results, and thus shed new insights on the design and deployment of future dense SCNs.

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 "will the area spectral efficiency monotonically grow as small cells go dense":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "modeling and performance analysis in cache enabled millimeter wave hetnets with access and backhaul integration")
  Member "a stochastic geometry framework for los nlos propagation in dense small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "energy efficient cooperative caching in uav networks")
  Member "analysis of blockage effects on urban cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")
  Member "offloading in heterogeneous networks modeling analysis and design insights":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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-8 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense 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.IT(Information Theory)