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: "massive mimo with 1 bit adc"
  Abstract: We investigate massive multiple-input-multiple output (MIMO) uplink systems with 1-bit analog-to-digital converters (ADCs) on each receiver antenna. Receivers that rely on 1-bit ADC do not need energy-consuming interfaces such as automatic gain control (AGC). This decreases both ADC building and operational costs. Our design is based on maximal ratio combining (MRC), zero-forcing (ZF), and least squares (LS) detection, taking into account the effects of the 1-bit ADC on channel estimation. Through numerical results, we show good performance of the system in terms of mutual information and symbol error rate (SER). Furthermore, we provide an analytical approach to calculate the mutual information and SER of the MRC receiver. The analytical approach reduces complexity in the sense that a symbol and channel noise vectors Monte Carlo simulation is avoided.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of quantized uplink massive mimo ofdm with oversampling under adjacent channel interference"):
  with members:
    - "massive mu mimo ofdm uplink with hardware impairments modeling and analysis"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "linear precoding with low resolution dacs for massive mu mimo ofdm downlink"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "mixed adc massive mimo detectors performance analysis and design optimization"
    - "massive mimo ten myths and one critical question"
    - "one bit massive mimo channel estimation and high order modulations"

Connected through hyperedge HE-2 (induced by source paper "new equivalent model of quantizer with noisy input and its application for adc resolution determination in an uplink mimo receiver"):
  with members:
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "full duplex massive mimo relaying systems with low resolution adcs"
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "mixed adc massive mimo detectors performance analysis and design optimization"
    - "quantized precoding for massive mu mimo"

Connected through hyperedge HE-3 (induced by source paper "autoencoder based error correction coding for one bit quantization"):
  with members:
    - "one bit ofdm receivers via deep learning"
    - "learning a code machine learning for approximate non linear coded computation"
    - "deepcode feedback codes via deep learning"
    - "deep learning methods for improved decoding of linear codes"
    - "an introduction to deep learning for the physical layer"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"
    - "on deep learning based channel decoding"

Connected through hyperedge HE-4 (induced by source paper "optimal multiuser loading in quantized massive mimo under spatially correlated channels"):
  with members:
    - "mixed adc dac multipair massive mimo relaying systems performance analysis and power optimization"
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "massive mimo downlink 1 bit precoding with linear programming for psk signaling"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"
    - "downlink achievable rate analysis in massive mimo systems with one bit dacs"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "quantized precoding for massive mu mimo"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-5 (induced by source paper "on the capacity of massive mimo with 1 bit adcs and dacs at the receiver and at the transmitter"):
  with members:
    - "on mimo channel capacity with output quantization constraints"
    - "a general framework for low resolution receivers for mimo channels"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "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"
    - "robust 1 bit compressive sensing via binary stable embeddings of sparse vectors"
    - "analysis of 1 bit output noncoherent fading channels in the low snr regime"

Connected through hyperedge HE-6 (induced by source paper "semi supervised learning detector for mu mimo systems with one bit adcs"):
  with members:
    - "a supervised learning detector for multihop distributed reception systems"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"

Connected through hyperedge HE-7 (induced by source paper "bayesian optimal data detector for hybrid mmwave mimo ofdm systems with low resolution adcs"):
  with members:
    - "resolution adaptive hybrid mimo architectures for millimeter wave communications"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "bayesian optimal data detector for mmwave ofdm system with low resolution adc"
    - "generalized expectation consistent signal recovery for nonlinear measurements"
    - "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"
    - "mixed adc massive mimo uplink in frequency selective channels"

Connected through hyperedge HE-8 (induced by source paper "performance analysis of multi cell millimeter wave massive mimo networks with low precision adcs"):
  with members:
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "a hardware efficient analog network structure for hybrid precoding in millimeter wave systems"
    - "a comparison of hybrid beamforming and digital beamforming with low resolution adcs for multiple users and imperfect csi"
    - "secure massive mimo systems with limited rf chains"
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "spectral and energy efficiency of multi pair massive mimo relay network with hybrid processing"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "base station selection for massive mimo networks with two stage precoding"

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)