human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "performance of a link in a field of vehicular interferers with hardcore headway distance"
  Abstract: The performance of vehicular networks have been largely assessed using the Poisson Point Process (PPP) to model the locations of vehicles along a road. The PPP is not always a realistic model, because it doesn't account for the safety distance a driver maintains from the vehicle ahead. In this paper, we model the inter-vehicle (or headway) distance equal to the sum of a constant hardcore distance and a random distance following the exponential distribution. Unfortunately, the probability generating functional of this point process is unknown. In order to approximate the Laplace transform of interference at the origin, we devise simple approximations for the variance and skewness of interference, and we select suitable probability functions to approximate the interference distribution. In some cases, the PPP (of equal intensity) gives a good approximation for the outage probability. When the coefficient-of-variation and the skewness of interference distribution are high, the PPP approximation becomes loose in the upper tail. Relevant scenarios are associated with urban microcells and highway macrocells with low intensity of vehicles. The predictions of PPP deteriorate with multi-antenna maximum ratio combining receiver and temporal indicators related to the performance of retransmission schemes. Our approximations generate good predictions in all considered cases.

Connected through hyperedge HE-1 (induced by source paper "the meta distribution of the sir in linear motorway vanets"):
  with members:
    - "outage in motorway multi lane vanets with hardcore headway distance using synthetic traces"
    - "moments of interference in vehicular networks with hardcore headway distance"
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "fine grained vs average reliability for v2v communications around intersections"
    - "the meta distribution of the sir for cellular networks with power control"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "the meta distribution of the sir in poisson bipolar and cellular networks"
    - "stochastic geometry modeling of cellular networks analysis simulation and experimental validation"

Connected through hyperedge HE-2 (induced by source paper "moments of interference in vehicular networks with hardcore headway distance"):
  with members:
    - "temporal correlation of interference and outage in mobile networks over one dimensional finite regions"
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "user point processes in cellular networks"
    - "statistical modeling and probabilistic analysis of cellular networks with determinantal point processes"
    - "rigorous high precision computation of the hurwitz zeta function and its derivatives"
    - "analytical modeling of uplink cellular networks"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"

Question: Please tell me which class the center node 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)