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 estimation and uplink achievable rates in one bit massive mimo systems"
  Abstract: This paper considers channel estimation and achievable rates for the uplink of a massive multiple-input multiple-output (MIMO) system where the base station is equipped with one-bit analog-to-digital converters (ADCs). By rewriting the nonlinear one-bit quantization using a linear expression, we first derive a simple and insightful expression for the linear minimum mean-square-error (LMMSE) channel estimator. Then employing this channel estimator, we derive a closed-form expression for the lower bound of the achievable rate for the maximum ratio combiner (MRC) receiver. Numerical results are presented to verify our analysis and show that our proposed LMMSE channel estimator outperforms the near maximum likelihood (nML) estimator proposed previously.

Connected through hyperedge HE-1 (induced by source paper "one bit ofdm receivers via deep learning"):
  with members:
    - "ofdm autoencoder for end to end learning of communications systems"
    - "an introduction to deep learning for the physical layer"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "bayesian optimal data detector for mmwave ofdm system with low resolution adc"
    - "detection algorithms for communication systems using deep learning"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"
    - "uplink performance of wideband massive mimo with one bit adcs"

Connected through hyperedge HE-2 (induced by source paper "capacity of multiple one bit transceivers in a rayleigh environment"):
  with members:
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "massive mu mimo ofdm downlink with one bit dacs and linear precoding"
    - "downlink achievable rate analysis in massive mimo systems with one bit dacs"
    - "mmse precoder for massive mimo using 1 bit quantization"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "quantized massive mu mimo ofdm uplink"
    - "analysis of 1 bit output noncoherent fading channels in the low snr regime"

Connected through hyperedge HE-3 (induced by source paper "beamforming with multiple one bit wireless transceivers"):
  with members:
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "massive mu mimo ofdm downlink with one bit dacs and linear precoding"
    - "downlink achievable rate analysis in massive mimo systems with one bit dacs"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "quantized massive mu mimo ofdm uplink"
    - "analysis of 1 bit output noncoherent fading channels in the low snr regime"

Connected through hyperedge HE-4 (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"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"

Connected through hyperedge HE-5 (induced by source paper "throughput analysis of massive mimo uplink with low resolution adcs"):
  with members:
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "mixed adc massive mimo"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "short packet communications over multiple antenna rayleigh fading channels"
    - "massive mimo ten myths and one critical question"
    - "one bit massive mimo channel estimation and high order modulations"
    - "uplink achievable rate for massive mimo systems with low resolution adc"

Connected through hyperedge HE-6 (induced by source paper "channel estimation and performance analysis of one bit massive mimo systems"):
  with members:
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "mixed adc massive mimo"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "performance of the wideband massive uplink mimo with one bit adcs"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "one bit massive mimo channel estimation and high order modulations"
    - "uplink achievable rate for massive mimo systems with low resolution adc"

Connected through hyperedge HE-7 (induced by source paper "low snr asymptotic rates of vector channels with one bit outputs"):
  with members:
    - "gaussian multiple access channels with one bit quantizer at the receiver"
    - "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"
    - "how much training is needed in one bit massive mimo systems at low snr"
    - "mixed adc massive mimo"
    - "one bit massive mimo channel estimation and high order modulations"
    - "joint channel and data estimation for large mimo systems with low precision adcs"

Connected through hyperedge HE-8 (induced by source paper "achievable uplink rates for massive mimo with coarse quantization"):
  with members:
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "how much training is needed in one bit massive mimo systems at low snr"
    - "massive mimo with low resolution adcs"
    - "mixed adc massive mimo"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "analysis of massive mimo with hardware impairments and different channel models"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"

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)