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: "modeling the interference generated from car base stations towards indoor femto cells"
  Abstract: Abstract   In future wireless networks, a significant number of users will be vehicular. One promising solution to improve the capacity for these vehicular users is to employ moving relays or car base stations. The system forms cell inside the vehicle and then uses rooftop antenna for backhauling to overcome the vehicular penetration loss. In this paper, we develop a model for aggregate interference distribution generated from moving/parked cars to indoor users in order to study whether indoor femto-cells can coexist on the same spectrum with vehicular communications. Since spectrum authorization for vehicular communications is open at moment, we consider two spectrum sharing scenarios (i) communication from mounted antennas on the roof of the vehicles to the infrastructure network utilizes same spectrum with indoor femto-cells (ii) in-vehicle communication utilizes same spectrum with indoor femto-cells while vehicular to infrastructure (V2I) communication is allocated at different spectrum. Based on our findings we suggest that V2I and indoor femto-cells should be allocated at different spectrum. The reason being that mounted roof-top antennas facing the indoor cells generate unacceptable interference levels. On the other hand, in-vehicle communication and indoor cells can share the spectrum thanks to the vehicle body isolation and the lower transmit power levels that can be used inside the vehicle.

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)