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: "a remark on channels with transceiver distortion"
  Abstract: Information transmission over channels with transceiver distortion is investigated via generalized mutual information (GMI) under Gaussian input distribution and nearest-neighbor decoding. A canonical transceiver structure in which the channel output is processed by a minimum mean-squared error estimator before decoding is established to maximize the GMI, and the well-known Bussgang's decomposition is shown to be a heuristic that is consistent with the GMI under linear output processing.

Connected through hyperedge HE-1 (induced by source paper "a regression approach to certain information transmission problems"):
  with members:
    - "learning to detect"
    - "mmwave beam prediction with situational awareness a machine learning approach"
    - "deep learning based channel estimation for beamspace mmwave massive mimo systems"
    - "one bit ofdm receivers via deep learning"
    - "deepcode feedback codes via deep learning"
    - "learning the mmse channel estimator"
    - "a model driven deep learning network for mimo detection"
    - "a two step learning and interpolation method for location based channel database"

Connected through hyperedge HE-2 (induced by source paper "resolution adaptive hybrid mimo architectures for millimeter wave communications"):
  with members:
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "mixed adc massive mimo"
    - "adc bit allocation under a power constraint for mmwave massive mimo communication receivers"
    - "channel estimation for millimeter wave massive mimo with hybrid precoding over frequency selective fading channels"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "channel estimation and uplink achievable rates in one bit massive mimo systems"

Connected through hyperedge HE-3 (induced by source paper "quantized precoding for massive mu mimo"):
  with members:
    - "1 bit massive mu mimo precoding in vlsi"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "massive mu mimo ofdm downlink with one bit dacs and linear precoding"
    - "nonlinear 1 bit precoding for massive mu mimo with higher order modulation"
    - "data detection in large multi antenna wireless systems via approximate semidefinite relaxation"
    - "no downlink pilots are needed in tdd massive mimo"

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)