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: "at low snr asymmetric quantizers are better"
  Abstract: We study the capacity of the discrete-time Gaussian channel when its output is quantized with a one-bit quantizer. We focus on the low signal-to-noise ratio (SNR) regime, where communication at very low spectral efficiencies takes place. In this regime a symmetric threshold quantizer is known to reduce channel capacity by a factor of 2/pi, i.e., to cause an asymptotic power loss of approximately two decibels. Here it is shown that this power loss can be avoided by using asymmetric threshold quantizers and asymmetric signaling constellations. To avoid this power loss, flash-signaling input distributions are essential. Consequently, one-bit output quantization of the Gaussian channel reduces spectral efficiency. Threshold quantizers are not only asymptotically optimal: at every fixed SNR a threshold quantizer maximizes capacity among all one-bit output quantizers. The picture changes on the Rayleigh-fading channel. In the noncoherent case a one-bit output quantizer causes an unavoidable low-SNR asymptotic power loss. In the coherent case, however, this power loss is avoidable provided that we allow the quantizer to depend on the fading level.

Connected through hyperedge HE-1 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints"):
  with members:
    - "tradeoff between delay and high snr capacity in quantized mimo systems"
    - "optimal errors and phase transitions in high dimensional generalized linear models"
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "on mimo channel capacity with output quantization constraints"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "a general framework for low resolution receivers for mimo channels"
    - "additivity of information in multilayer networks via additive gaussian noise transforms"
    - "generalized expectation consistent signal recovery for nonlinear measurements"

Connected through hyperedge HE-2 (induced by source paper "entropy constrained maximizing mutual information quantization"):
  with members:
    - "dynamic programming for discrete memoryless channel quantization"
    - "minimizing impurity partition under constraints"
    - "how to construct polar codes"
    - "quantization of binary input discrete memoryless channels"

Connected through hyperedge HE-3 (induced by source paper "on multiterminal communication over mimo channels with one bit adcs at the receivers"):
  with members:
    - "tradeoff between delay and high snr capacity in quantized mimo systems"
    - "gaussian multiple access channels with one bit quantizer at the receiver"
    - "on mimo channel capacity with output quantization constraints"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "quantized massive mu mimo ofdm uplink"
    - "millimeter wave cellular wireless networks potentials and challenges"

Connected through hyperedge HE-4 (induced by source paper "tradeoff between delay and high snr capacity in quantized mimo systems"):
  with members:
    - "on multiterminal communication over mimo channels with one bit adcs at the receivers"
    - "on mimo channel capacity with output quantization constraints"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "millimeter wave cellular wireless networks potentials and challenges"

Connected through hyperedge HE-5 (induced by source paper "bandlimited communication with one bit quantization and oversampling transceiver design and performance evaluation"):
  with members:
    - "spatio temporal waveform design for multiuser massive mimo downlink with 1 bit receivers"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "spectral efficient communications employing 1 bit quantization and oversampling at the receiver"
    - "a general framework for transmission with transceiver distortion and some applications"
    - "increased capacity per unit cost by oversampling"

Connected through hyperedge HE-6 (induced by source paper "reconsidering linear transmit signal processing in 1 bit quantized multi user miso systems"):
  with members:
    - "1 bit massive mu mimo precoding in vlsi"
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"
    - "massive mimo downlink 1 bit precoding with linear programming for psk signaling"
    - "massive mu mimo ofdm downlink with one bit dacs and linear precoding"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"
    - "nonlinear 1 bit precoding for massive mu mimo with higher order modulation"
    - "downlink achievable rate analysis in massive mimo systems with one bit dacs"
    - "minimum ber precoding in 1 bit massive mimo systems"

Connected through hyperedge HE-7 (induced by source paper "information distilling quantizers"):
  with members:
    - "strong data processing inequalities for channels and bayesian networks"
    - "opening the black box of deep neural networks via information"
    - "greedy merge degrading has optimal power law"
    - "bounds on the entropy of a function of a random variable and their applications"
    - "on the construction of polar codes for channels with moderate input alphabet sizes"
    - "justification of logarithmic loss via the benefit of side information"
    - "deep learning and the information bottleneck principle"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"

Connected through hyperedge HE-8 (induced by source paper "performance analysis for channel estimation with 1 bit adc and unknown quantization threshold"):
  with members:
    - "performance analysis for time of arrival estimation with oversampled low complexity 1 bit a d conversion"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "performance analysis for pilot based 1 bit channel estimation with unknown quantization threshold"
    - "doa parameter estimation with 1 bit quantization bounds methods and the exponential replacement"
    - "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"
    - "asymptotic parameter tracking performance with measurement data of 1 bit resolution"

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)