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: "doppler spectrum analysis of a roadside scatterer model for vehicle to vehicle channels an indirect method"
  Abstract: In vehicle-to-vehicle (V2V) channels, such roadside scatterers (RSSs) as houses, buildings, trees, and many more, play a crucial role in the determination of the Doppler power spectral density (DPSD) characteristics. However, the relevant research results are scarce due to the lack of computationally tractable analytic DPSD solutions. To fill this gap, we investigate an indirect method for the DPSD analysis of a generic two-dimensional (2D) RSS model for V2V channels. The indirect method, based on the Hoeher's theorem, employs successive transformations of random variables to obtain the DPSD. Compared to the conventional methods, leading to impractical multiple integral solutions, our method yields a single integral-form, more useful for analytic studies, model validation/parameter estimation, and fading simulator design. Using the new DPSD solution, the impact of different RSS layouts on the DPSD characteristics is further investigated, and several new insights are provided. The joint probability density function (PDF) of angle-of-departure and angle-of-arrival (AoA) and the joint Doppler-AoA PDF are newly presented in closed-forms and analyzed with respect to the DPSD shape. Comparisons with the DPSDs measured in highway and \FB{urban canyon} environments demonstrate not only the validity of the generic 2D RSS model, but also the significant contribution of RSSs to V2V channels.

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.IT(Information Theory)