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: "reciprocity calibration for massive mimo proposal modeling and validation"
  Abstract: This paper presents a mutual coupling based calibration method for time-division-duplex massive MIMO systems, which enables downlink precoding based on uplink channel estimates. The entire calibration procedure is carried out solely at the base station (BS) side by sounding all BS antenna pairs. An Expectation-Maximization (EM) algorithm is derived, which processes the measured channels in order to estimate calibration coefficients. The EM algorithm outperforms current state-of-the-art narrow-band calibration schemes in a mean squared error (MSE) and sum-rate capacity sense. Like its predecessors, the EM algorithm is general in the sense that it is not only suitable to calibrate a co-located massive MIMO BS, but also very suitable for calibrating multiple BSs in distributed MIMO systems. #R##N#The proposed method is validated with experimental evidence obtained from a massive MIMO testbed. In addition, we address the estimated narrow-band calibration coefficients as a stochastic process across frequency, and study the subspace of this process based on measurement data. With the insights of this study, we propose an estimator which exploits the structure of the process in order to reduce the calibration error across frequency. A model for the calibration error is also proposed based on the asymptotic properties of the estimator, and is validated with measurement results.

Connected through hyperedge HE-1 (induced by source paper "amplitude and phase estimation for absolute calibration of massive mimo front ends"):
  with members:
    - "a framework for over the air reciprocity calibration for tdd massive mimo systems"
    - "impact of line of sight and unequal spatial correlation on uplink mu mimo systems"
    - "hybrid beamforming for massive mimo a survey"
    - "massive mimo in real propagation environments do all antennas contribute equally"
    - "massive mimo for next generation wireless systems"
    - "scalable synchronization and reciprocity calibration for distributed multiuser mimo"

Connected through hyperedge HE-2 (induced by source paper "deep learning for ul dl channel calibration in generic massive mimo systems"):
  with members:
    - "energy efficient multi user miso communication using low resolution large intelligent surfaces"
    - "achievable rate maximization by passive intelligent mirrors"
    - "asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions"
    - "a framework for over the air reciprocity calibration for tdd massive mimo systems"
    - "neural offset min sum decoding"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
    - "learning to communicate channel auto encoders domain specific regularizers and attention"
    - "effective approaches to attention based neural machine translation"

Connected through hyperedge HE-3 (induced by source paper "local partial zero forcing precoding for cell free massive mimo"):
  with members:
    - "scalability aspects of cell free massive mimo"
    - "ubiquitous cell free massive mimo communications"
    - "making cell free massive mimo competitive with mmse processing and centralized implementation"
    - "downlink spectral efficiency of cell free massive mimo with full pilot zero forcing"
    - "cell free massive mimo with limited backhaul"
    - "on the total energy efficiency of cell free massive mimo"
    - "cell free massive mimo versus small cells"
    - "are we approaching the fundamental limits of wireless network densification"

Connected through hyperedge HE-4 (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:
    - "channel reciprocity calibration in tdd hybrid beamforming massive mimo systems"
    - "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"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "beyond 5g leveraging cell free tdd massive mimo using cascaded deep learning"):
  with members:
    - "an introduction to deep learning for the physical layer"
    - "a framework for over the air reciprocity calibration for tdd massive mimo systems"
    - "massive mimo performance with imperfect channel reciprocity and channel estimation error"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"
    - "cell free massive mimo versus small cells"

Connected through hyperedge HE-6 (induced by source paper "on reciprocity in physically consistent tdd systems with coupled antennas"):
  with members:
    - "massive mimo for next generation wireless systems"
    - "a general rate duality of the mimo multiple access channel and the mimo broadcast channel"

Connected through hyperedge HE-7 (induced by source paper "efficient dsp and circuit architectures for massive mimo state of the art and future directions"):
  with members:
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "out of band radiation from antenna arrays clarified"
    - "spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities"
    - "decentralized baseband processing for massive mu mimo systems"
    - "performance characterization of a real time massive mimo system with los mobile channels"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "on out of band emissions of quantized precoding in massive mu mimo ofdm"
    - "achievable uplink rates for massive mimo with coarse quantization"

Connected through hyperedge HE-8 (induced by source paper "ieee 802 11ay based mmwave wlans design challenges and solutions"):
  with members:
    - "performance analysis of integrated sub 6 ghz millimeter wave wireless local area networks"
    - "beamspace su mimo for future millimeter wave wireless communications"
    - "ieee 802 11ax high efficiency wlans"
    - "initial access in 5g mmwave cellular networks"
    - "flexible dual connectivity spectrum aggregation for decoupled uplink and downlink access in 5g heterogeneous systems"
    - "joint millimeter wave and microwave resources allocation in cellular networks with dual mode base stations"
    - "beam searching and transmission scheduling in millimeter wave communications"
    - "60 ghz mac standardization progress and way forward"

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)