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 the local quasi stationarity of measured dual polarized mimo channels"
  Abstract: It is common practice in wireless communications to assume strict or wide-sense stationarity of the wireless channel in time and frequency. While this approximation has some physical justification, it is only valid inside certain time–frequency regions. This paper presents an elaborate characterization of the non-stationarity of wireless dual-polarized (DP) channels in time. The evaluation is based on urban macrocell measurements performed at 2.53 GHz. To define local quasi-stationarity (LQS) regions, i.e., regions in which the change of certain channel statistics is deemed insignificant, we resort to the performance degradation of selected algorithms specific to channel estimation and beamforming. Additionally, we compare our results to commonly used measures in the literature. We find that the polarization, the antenna spacing, and the opening angle of the antennas into the propagation channel can strongly influence the non-stationarity of the observed channel. The obtained LQS regions can be of significant size, i.e., several meters; thus, the reuse of channel statistics over large distances is meaningful (in an average sense) for the considered correlation-based algorithms. Furthermore, we conclude that, from a system perspective, a proper non-stationarity analysis should be based on the considered algorithm.

Connected through hyperedge HE-1 (induced by source paper "tutorial on uav a blue sky view on wireless communication"):
  with members:
    - "cellular connectivity for uavs network modeling performance analysis and design guidelines"
    - "energy constrained uav trajectory design for ground node localization"
    - "comp in the sky uav placement and movement optimization for multi user communications"
    - "key technologies and system trade offs for detection and localization of amateur drones"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "aerial anchors positioning for reliable rss based outdoor localization in urban environments"
    - "an overview of 3gpp release 15 study on enhanced lte support for connected drones"
    - "ultra reliable uav communication using altitude and cooperation diversity"

Connected through hyperedge HE-2 (induced by source paper "hybrid beamforming with selection for multiuser massive mimo systems"):
  with members:
    - "stationarity region of mm wave channel based on outdoor microcellular measurements at 28 ghz"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "5g 3gpp like channel models for outdoor urban microcellular and macrocellular environments"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "massive mimo combining with switches"
    - "hybrid beamforming for massive mimo a survey"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"

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)