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 "stochastic geometry modeling of cellular v2x communication over shared channels"):
  Abstract: To overcome the limitations of DSRC with short range, non-supportability of high density networks, unreliable broadcast services, signal congestion and connectivity disruptions, cellular vehicle-to-everything (C-V2X) communication networks, standardized in 3rd Generation Partnership Project (3GPP) Release 14, have been recently introduced to cover broader vehicular communication scenarios including vehicle-to-vehicle (V2V), vehicle-to-pedestrian (V2P) and vehicle-to-infrastructure/network (V2I/N). In C-V2X, vehicles can directly communicate over PC5 based dedicated sidelinks called direct mode or V2V communication. However, high vehicle densities may require reuse of cellular spectrum for V2V. Moreover, infrastructure mode communication through V2I/N links can augment V2V communication by enhancing communication range and reliability for enhanced safety along with consistent performance under traffic congestions. Motivated by the stringent connection reliability, spectral efficiency, and coverage requirements in C-V2X, this paper presents the first comprehensive and tractable analytical framework for performance of C-V2X networks over shared V2V and cellular uplink channels, where the transmitting vehicles can deliver their information via infrastructure or direct mode, based on their distances, propagation environments and the bias factor. By practically modeling the vehicles on the roads using the doubly stochastic Cox process and the base-stations, we derive new association probabilities, new success probabilities of infrastructure and direct mode, and overall success probability of the C-V2X communication over shared channels, which are validated by the simulations results. Our results reveal the benefits of our proposed model (possibility of selecting both direct and infrastructure modes over shared channels) compared to V2V network in terms of success probability.

Includes members:
  Member "success probability and area spectral efficiency of a vanet modeled as a cox process":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coverage and rate analysis of downlink cellular vehicle to everything c v2x communication")
  Member "an analytical framework for coverage in cellular networks leveraging vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how to dimension radio resources when users are distributed on roads modeled by poisson line process")
  Member "coverage analysis of a vehicular network modeled as cox process driven by poisson line process":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how to dimension radio resources when users are distributed on roads modeled by poisson line process")
  Member "asymptotic blind spot analysis of localization networks under correlated blocking using a poisson line process":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "a primer on cellular network analysis using stochastic geometry":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "artificial noise aided secure transmission in large scale spectrum sharing networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "physical layer security in three tier wireless sensor networks a stochastic geometry approach":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secure and energy efficient transmissions in cache enabled heterogeneous cellular networks performance analysis and optimization")
  Member "d2d based v2v communications with latency and reliability constraints":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed federated learning for ultra reliable low latency vehicular communications")

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)