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: "analysis of large scale propagation models for mobile communications in urban area"
  Abstract: Channel properties influence the development of wireless communication systems. Unlike wired channels that are stationary and predictable, radio channels are extremely random and dont offer easy analysis. A Radio Propagation Model (RPM), also known as the Radio Wave Propagation Model (RWPM), is an empirical mathematical formulation for the characterization of radio wave propagation as a function of frequency. In mobile radio systems, path loss models are necessary for proper planning, interference estimations, frequency assignments and cell parameters which are the basic for network planning process as well as Location Based Services (LBS) techniques. Propagation models that predict the mean signal strength for an arbitrary transmitter receiver (T R) separation distance which is useful in estimating the radio coverage area of a transmitter are called large scale propagation models, since they characterize signal strength over large TR separation distances. In this paper, the large scale propagation performance of Okumura, Hata, and Lee models has been compared varying Mobile Station (MS) antenna height, Transmitter Receiver (TR) distance and Base Station (BS) antenna height, considering the system to operate at 900 MHz. Through the MATLAB simulation it is turned out that the Okumura model shows the better performance than that of the other large scale propagation models.

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)