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 "the meta distribution of the sir in linear motorway vanets"):
  Abstract: The meta distribution of the signal-to-interference-ratio (SIR) is an important performance indicator for wireless networks because, for ergodic point processes, it describes the fraction of scheduled links that achieve certain reliability, conditionally on the point process. The calculation of the moments of the meta distribution requires the probability generating functional (PGFL) of the point process. In vehicular ad hoc networks (VANETs) along high-speed motorways, the Poisson point process (PPP) is a poor deployment model, because the drivers, due to the high speeds, maintain large safety distances. In this paper, we model the distribution of inter-vehicle distance equal to the sum of a constant hardcore distance and an exponentially distributed random variable. We design a novel \emph{discretization model} for the locations of vehicles which can be used to approximate well the PGFL due to the hardcore point process and the meta distribution of the SIR generated from synthetic motorway traces. On the other hand, the PPP overestimates significantly the coefficient-of-variation of the meta distribution due to the hardcore process, and its predictions fail. In addition, we show that the calculation of the meta distribution becomes especially meaningful in the upper tail of the SIR distribution.

Includes members:
  Member "outage in motorway multi lane vanets with hardcore headway distance using synthetic traces":
    also connected through other hyperedges:
      (none)
  Member "moments of interference in vehicular networks with hardcore headway distance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "temporal correlation of interference in vehicular networks with shifted exponential time headways")
  Member "performance of a link in a field of vehicular interferers with hardcore headway distance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "moments of interference in vehicular networks with hardcore headway distance")
  Member "an analytical framework for coverage in cellular networks leveraging vehicles":
    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 "fine grained vs average reliability for v2v communications around intersections":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks")
  Member "the meta distribution of the sir for cellular networks with power control":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a spatiotemporal framework for information freshness in iot uplink networks")
  Member "coverage analysis of a vehicular network modeled as cox process driven by poisson line process":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "how to dimension radio resources when users are distributed on roads modeled by poisson line process")
  Member "the meta distribution of the sir in poisson bipolar and cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "spatio temporal modeling for massive and sporadic access")

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)