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: "capacity delay scaling in arbitrary wireless networks"
  Abstract: We establish capacity and delay scaling laws for a general network topology, interference model, and traffic model. There are two main contributions of this paper. Our first contribution is the derivation of capacity-delay scaling laws in terms of spectral properties of the wireless network using results of Diaconis and Stroock (1991) and Sinclair (1992). By representing a wireless network in terms of an appropriate capacitated graph, we determine precise (i.e. upper and lower bound) capacity scaling in terms of the maximal min-cut capacity over a class of graphs. Next, we establish delay scaling using very simple techniques. Our methods apply to general fixed and mobile network models. As a special case, we recover the results of Gupta and Kumar (2000), El Gamal, Mammen, Prabhakar and Shah (2004), Grossglauser and Tse (2002) and Diggavi, Grossglauser and Tse (2003). #R##N#The second contribution is the derivation of capacity scaling laws for Gaussian channels. In particular, we provide upper and lower bounds on capacity scaling for an arbitrary wireless network with AWGN channels and non-cooperative transmissions. We characterize the capacity scaling for non-cooperative transmissions in terms of the cut-properties of the underlying network graph. We also provide information theoretic upper bounds for general fading AWGN channels. Finally, we evaluate our bounds for grid graph and geometric random graph.

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)