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: "power optimal non contiguous spectrum access"
  Abstract: Wireless transmission using non-contiguous chunks of spectrum is becoming increasingly important due to a variety of scenarios such as: secondary users avoiding incumbent users in TV white space; anticipated spectrum sharing between commercial and military systems; and spectrum sharing among uncoordinated interferers in unlicensed bands. Multi-Channel Multi-Radio (MCMR) platforms and Non-Contiguous Orthogonal Frequency Division Multiple Access (NC-OFDMA) technology are the two commercially viable transmission choices to access these non-contiguous spectrum chunks. Fixed MC-MRs do not scale with increasing number of non-contiguous spectrum chunks due to their fixed set of supporting radio front ends. NC-OFDMA allows nodes to access these non-contiguous spectrum chunks and put null sub-carriers in the remaining chunks. However, nulling sub-carriers increases the sampling rate (spectrum span) which, in turn, increases the power consumption of radio front ends. Our work characterizes this trade-off from a cross-layer perspective, specifically by showing how the slope of ADC/DAC power consumption versus sampling rate curve influences scheduling decisions in a multi-hop network. Specifically, we provide a branch and bound algorithm based mixed integer linear programming solution that performs joint power control, spectrum span selection, scheduling and routing in order to minimize the system power of multi-hop NC-OFDMA networks. We also provide a low complexity (O(E^2 M^2)) greedy algorithm where M and E denote the number of channels and links respectively. Numerical simulations suggest that our approach reduces system power by 30% over classical transmit power minimization based cross-layer algorithms.

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)