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: "packet reception probabilities in vehicular communications close to intersections"
  Abstract: Vehicular networks allow vehicles to share information and are expected to be an integral part in future intelligent transportation system (ITS). In order to guide and validate the design process, analytical expressions of key performance metrics such as packet reception probabilities and throughput are necessary, in particular for accident-prone scenarios such as intersections. In this paper, we analyze the impact of interference in an intersection scenario with two perpendicular roads using tools from stochastic geometry. We present a general procedure to analytically determine the packet reception probability and throughput of a selected link, taking into account the geographical clustering of vehicles close to the intersection. We consider both Aloha and CSMA MAC protocols, and show how the procedure can be used to model different propagation environments of practical relevance. We show how different path loss functions and fading distributions can be incorporated in the analysis to model propagation conditions typical to both rural and urban intersections. Our results indicate that the procedure is general and flexible to deal with a variety of scenarios. Thus, it can serve as a useful design tool for communication system engineers, complementing simulations and experiments, to obtain quick insights into the network performance.

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.SY(Systems and Control)