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: "channel reciprocity calibration in tdd hybrid beamforming massive mimo systems"
  Abstract: A hybrid analog–digital (AD) beamforming structure is a very attractive solution to build low-cost massive multiple-input multiple-output systems. Typically, these systems use a set of fixed beams for transmission and reception to avoid the need to obtain channel state information at transmitter (CSIT) for each antenna element individually. However, such a method cannot fully exploit the potential of hybrid AD beamforming systems. Alternatively, CSIT can be estimated by assuming a model for the propagation channel, whereas this model is only validated in millimeter-wave band; thanks to its poor scattering nature. In this paper, we focus on time division duplex systems with hybrid beamforming structure and propose a reciprocity calibration scheme that allows to acquire full CSIT. Different from existing CSIT acquisition methods, our approach does not require any assumption on the channel model and can estimate full CSIT.

Connected through hyperedge HE-1 (induced by source paper "achieving phase coherency and gain stability in active antenna arrays for sub 6 ghz fdd and tdd fd mimo challenges and solutions"):
  with members:
    - "a framework for over the air reciprocity calibration for tdd massive mimo systems"
    - "toward a realistic assessment of multiple antenna hcns residual additive transceiver hardware impairments and channel aging"
    - "overview of full dimension mimo in lte advanced pro"
    - "massive mimo performance with imperfect channel reciprocity and channel estimation error"
    - "reciprocity calibration for massive mimo proposal modeling and validation"
    - "uplink performance of time reversal mrc in massive mimo systems subject to phase noise"
    - "massive mimo with non ideal arbitrary arrays hardware scaling laws and circuit aware design"

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)