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: "on the co existence of td lte and radar over 3 5 ghz band an experimental study"
  Abstract: This letter presents a pioneering study based on a series of experiments on the operation of commercial Time-Division Long-Term Evolution (TD-LTE) systems in the presence of pulsed interfering signals in the 3550-3650 MHz band. TD-LTE operations were carried out in channels overlapping and adjacent to the high power SPN-43 radar with various frequency offsets between the two systems to evaluate the susceptibility of LTE to a high power interfering signal. Our results demonstrate that LTE communication using low antenna heights was not adversely affected by the pulsed interfering signal operating on adjacent frequencies irrespective of the distance of interfering transmitter. Performance was degraded only for very close distances (1-2 km) of overlapping frequencies of interfering transmitter.

Connected through hyperedge HE-1 (induced by source paper "coexistence of radar and communication systems in cbrs bands through downlink power control"):
  with members:
    - "how close can i be a comprehensive analysis of cellular interference on atc radar"

Connected through hyperedge HE-2 (induced by source paper "coexistence of outdoor wi fi and radar at 3 5 ghz"):
  with members:
    - "spectrum sharing between a surveillance radar and secondary wi fi networks"

Connected through hyperedge HE-3 (induced by source paper "spectrum sharing radar coexistence via xampling"):
  with members:
    - "analog to digital cognitive radio sampling detection and hardware"
    - "performance of time delay estimation in a cognitive radar"
    - "sub nyquist cyclostationary detection for cognitive radio"
    - "sub nyquist channel estimation over ieee 802 11ad link"
    - "spectrum sharing between a surveillance radar and secondary wi fi networks"
    - "recursive recovery of sparse signal sequences from compressive measurements a review"
    - "sub nyquist sampling for power spectrum sensing in cognitive radios a unified approach"
    - "pattern coupled sparse bayesian learning for recovery of block sparse signals"

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)