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 "on the performance of practical ultra dense networks the major and minor factors"):
  Abstract: In this paper, we conduct performance evaluation for Ultra-Dense Networks (UDNs), and identify which modelling factors play major roles and minor roles. From our study, we draw the following conclusions. First, there are 3 factors/models that have a major impact on the performance of UDNs, and they should be considered when performing theoretical analyses: i) a multi-piece path loss model with line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions; ii) a non-zero antenna height difference between base stations (BSs) and user equipments (UEs); iii) a finite BS/UE density. Second, there are 4 factors/models that have a minor impact on the performance of UDNs, i.e., changing the results quantitatively but not qualitatively, and thus their incorporation into theoretical analyses is less urgent: i) a general multi-path fading model based on Rician fading; ii) a correlated shadow fading model; iii) a BS density dependent transmission power; iv) a deterministic BS/user density. Finally, there are 5 factors/models for future study: i) a BS vertical antenna pattern; ii) multi-antenna and/or multi-BS joint transmissions; iii) a proportional fair BS scheduler; iv) a non-uniform distribution of BSs; v) a dynamic time division duplex (TDD) or full duplex (FD) network. Our conclusions can guide researchers to down-select the assumptions in their theoretical analyses, so as to avoid unnecessarily complicated results, while still capturing the fundamentals of UDNs in a meaningful way.

Includes members:
  Member "study on the idle mode capability with los and nlos transmissions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cellular connectivity for uavs network modeling performance analysis and design guidelines")
  Member "microscopic analysis of the uplink interference in fdma small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "promises and caveats of uplink iot ultra dense networks")
  Member "throughput and coverage for a mixed full and half duplex small cell network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "backhaul aware uplink communications in full duplex dbs aided hetnets")
  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 los and nlos transmissions in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mobility in the sky performance and mobility analysis for cellular connected uavs")
  Member "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks")
  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 "d2d enhanced heterogeneous cellular networks with dynamic tdd":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")

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)