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: "downlink achievable rate analysis in massive mimo systems with one bit dacs"
  Abstract: In this letter, we investigate the downlink performance of massive multiple-input multiple-output (MIMO) systems where the base station is equipped with one-bit analogto-digital/digital-to-analog converters (ADC/DACs). Considering training-based transmission, we assume the base station (BS) employs the linear minimum mean-squared-error (LMMSE) channel estimator and treats the channel estimate as the true channel to precode the data symbols. We derive an expression for the downlink achievable rate for matched-filter (MF) precoding. A detailed analysis of the resulting power efficiency is pursued using our expression of the achievable rate. Numerical results are presented to verify our analysis. In particular it is shown that, compared with conventional massive MIMO systems, the performance loss in one-bit massive MIMO systems can be compensated for by deploying approximately 2.5 times more antennas at the BS.

Connected through hyperedge HE-1 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo"):
  with members:
    - "one bit sigma delta mimo precoding"
    - "a framework for one bit and constant envelope precoding over multiuser massive miso channels"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "secure massive mimo communication with low resolution dacs"):
  with members:
    - "optimal multiuser loading in quantized massive mimo under spatially correlated channels"
    - "mimo channel information feedback using deep recurrent network"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "spectral and energy efficiency of multi pair massive mimo relay network with hybrid processing"
    - "power efficient and secure wpcns with hardware impairments and non linear eh circuit"
    - "a tractable framework for performance analysis of dense multi antenna networks"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"

Connected through hyperedge HE-3 (induced by source paper "one bit sigma delta mimo precoding"):
  with members:
    - "symbol level precoding is symbol perturbed zf when energy efficiency is sought"
    - "a framework for one bit and constant envelope precoding over multiuser massive miso channels"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "multiuser one bit massive mimo precoding under mpsk signaling"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
    - "1 bit massive mu mimo precoding in vlsi"
    - "throughput analysis of massive mimo uplink with low resolution adcs"

Connected through hyperedge HE-4 (induced by source paper "neural network optimized 1 bit precoding for massive mu mimo"):
  with members:
    - "a deep learning framework for optimization of miso downlink beamforming"
    - "multilevel mimo detection with deep learning"
    - "one bit massive mimo precoding via a minimum symbol error probability design"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "trainable projected gradient detector for massive overloaded mimo channels data driven tuning approach"
    - "a model driven deep learning network for mimo detection"
    - "amp inspired deep networks for sparse linear inverse problems"
    - "1 bit massive mu mimo precoding in vlsi"

Connected through hyperedge HE-5 (induced by source paper "timing and frequency synchronization for 1 bit massive mu mimo ofdm downlink"):
  with members:
    - "directional frame timing synchronization in wideband millimeter wave systems with low resolution adcs"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "1 bit massive mu mimo precoding in vlsi"
    - "performance analysis for time of arrival estimation with oversampled low complexity 1 bit a d conversion"
    - "quantized precoding for multi antenna downlink channels with magiq"
    - "nonlinear precoding for phase quantized constant envelope massive mu mimo ofdm"
    - "joint cfo and channel estimation in millimeter wave systems with one bit adcs"
    - "linear precoding with low resolution dacs for massive mu mimo ofdm downlink"

Connected through hyperedge HE-6 (induced by source paper "training for channel estimation in nonlinear multi antenna transceivers"):
  with members:
    - "beamforming with multiple one bit wireless transceivers"
    - "capacity of multiple one bit transceivers in a rayleigh environment"
    - "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"
    - "how much training is needed in one bit massive mimo systems at low snr"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "mmse precoder for massive mimo using 1 bit quantization"

Connected through hyperedge HE-7 (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"
    - "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"
    - "massive mimo with 1 bit adc"

Connected through hyperedge HE-8 (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"

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)