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 "geometry based vehicle to vehicle channel modeling for large scale simulation"):
  Abstract: Due to the dynamic nature of vehicular traffic and the road surroundings, vehicle-to-vehicle (V2V) propagation characteristics vary greatly on both small and large scale. Recent measurements have shown that both large static objects (e.g., buildings and foliage) and mobile objects (surrounding vehicles) have a profound impact on V2V communication. At the same time, system-level vehicular ad hoc network (VANET) simulators by and large employ simple statistical propagation models, which do not account for surrounding objects explicitly. We designed Geometry-based Efficient propagation Model for V2V communication (GEMV#N# 2#N#), which uses outlines of vehicles, buildings, and foliage to distinguish the following three types of links: line of sight (LOS), non-LOS (NLOS) due to vehicles, and NLOS due to static objects. For each link, GEMV#N# 2#N# calculates the large-scale signal variations deterministically, whereas the small-scale signal variations are calculated stochastically based on the number and size of surrounding objects. We implement GEMV#N# 2#N# in MATLAB and show that it scales well by using it to simulate radio propagation for city-wide networks with tens of thousands of vehicles on commodity hardware. We make the source code of GEMV#N# 2#N# freely available. Finally, we validate GEMV#N# 2#N# against extensive measurements performed in urban, suburban, highway, and open-space environments.

Includes members:
  Member "a measurement based shadow fading model for vehicle to vehicle network simulations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a measurement based multilink shadowing model for v2v network simulations of highway scenarios")
  Member "delay and doppler spreads of nonstationary vehicular channels for safety relevant scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "toward intelligent vehicular networks a machine learning framework")
  Member "tvr tall vehicle relayingin vehicular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a measurement based multilink shadowing model for v2v network simulations of highway scenarios")

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)