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: "path loss and directional gain measurements at 28 ghz for non line of sight coverage of indoors with corridors"
  Abstract: Adequate coverage with high gain antennas is key to realizing the full promise of the bandwidth available at mm/cm wave bands. We report extensive indoor measurements at 28 GHz (1000 links, 9.9 million individual power measurements, 10 offices, 2 buildings), with/without line-of-sight (LOS) using a continuous wave channel sounder, with a 10o spinning horn, capable of capturing a full azimuth scan every 200 ms, in up to 171 dB path loss to characterize coverage with 90% confidence level. The environment had prominent corridors and rooms, as opposed to open/mixed offices in latest 3GPP standards. Guiding in corridors leads to much lower RMS azimuth spread (7 degree median in corridor non-LOS vs. 42 degree in 3GPP) and higher penetration loss into rooms and around corners (30-32 dB, some 12 dB more loss than 3GPP at 20 m non-LOS). Measured path gain in non-LOS is predicted by a mode-diffusion model with 3.9 dB RMS error. Scattering degraded azimuth gain by up to 4 dB in the corridor and 7 dB in rooms with 90% probability. Link simulations in a canonical building indicate every corridor needs an access point to provide 1 Gbps rate to adjoining rooms within 50 m using 400 MHz of bandwidth.

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)