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 "ultra dense networks is there a limit to spatial spectrum reuse"):
  Abstract: The aggressive spatial spectrum reuse (SSR) by network densification using smaller cells has successfully driven the wireless communication industry onward in the past decades. In our future journey toward ultra-dense networks (UDNs), a fundamental question needs to be answered. Is there a limit to SSR? In other words, when we deploy thousands or millions of small cell base stations (BSs) per square kilometer, is activating all BSs on the same time/frequency resource the best strategy? In this paper, we present theoretical analyses to answer such question. In particular, we find that both the signal and interference powers become bounded in practical UDNs with a non-zero BS-to-UE antenna height difference and a finite UE density, which leads to a constant capacity scaling law. As a result, there exists an optimal SSR density that can maximize the network capacity. Hence, the limit to SSR should be considered in the operation of future UDNs.

Includes members:
  Member "performance analysis of ultra dense networks with elevated base stations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal base station antenna downtilt in downlink cellular networks")
  Member "on the performance of practical ultra dense networks the major and minor factors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges")
  Member "performance impact of base station antenna heights in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks":
    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 "performance impact of idle mode capability on dense small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges")
  Member "performance impact of los and nlos transmissions in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mobility in the sky performance and mobility analysis for cellular connected uavs")
  Member "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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-8 (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)