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: "overdemodulation for high performance receivers with low resolution adc"
  Abstract: The design of the analog demodulator for receivers with low-resolution analog-to-digital converters (ADC) is investigated. For infinite ADC resolution, demodulation to baseband with M = 2 orthogonal sinusoidal functions (quadrature demodulation) is an optimum design choice. For receive systems which are restricted to ADC with low amplitude resolution we show here that this classical demodulation approach is suboptimal. To this end we analyze the theoretical channel parameter estimation performance based on a simple pessimistic characterization of the Fisher information measure when forming M > 2 analog demodulation channels prior to an ADC with 1-bit amplitude resolution. In order to emphasize that this inside is also true for communication problems, we provide an additional discussion on the behavior of the Shannon information measure under overdemodulation and 1-bit quantization.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of mixed adc massive mimo systems over rician fading channels"):
  with members:
    - "spatio temporal waveform design for multiuser massive mimo downlink with 1 bit receivers"
    - "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"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "distributed spatial multiplexing systems with hardware impairments and imperfect channel estimation under rank 1 rician fading channels"
    - "mixed adc massive mimo detectors performance analysis and design optimization"

Connected through hyperedge HE-2 (induced by source paper "wireless channel estimation with low complexity 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"
    - "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"
    - "one bit massive mimo channel estimation and high order modulations"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "performance analysis for time of arrival estimation with oversampled low complexity 1 bit a d conversion"):
  with members:
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "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"
    - "one bit massive mimo channel estimation and high order modulations"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "fisher information bounds with applications in nonlinear learning compression and inference"
    - "multiple parameter estimation with quantized channel output"
    - "increased capacity per unit cost by oversampling"

Connected through hyperedge HE-4 (induced by source paper "performance analysis for pilot based 1 bit channel estimation with unknown quantization threshold"):
  with members:
    - "at low snr asymmetric quantizers are better"
    - "increased capacity per unit cost by oversampling"

Connected through hyperedge HE-5 (induced by source paper "measurement driven quality assessment of nonlinear systems by exponential replacement"):
  with members:
    - "a lower bound for the fisher information measure"

Connected through hyperedge HE-6 (induced by source paper "fisher information bounds with applications in nonlinear learning compression and inference"):
  with members:
    - "a pessimistic approximation for the fisher information measure"
    - "measurement driven quality assessment of nonlinear systems by exponential replacement"
    - "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"
    - "a lower bound for the fisher information measure"
    - "gaussian assumption the least favorable but the most useful lecture notes"

Connected through hyperedge HE-7 (induced by source paper "asymptotic parameter tracking performance with measurement data of 1 bit resolution"):
  with members:
    - "a general framework for transmission with transceiver distortion and some applications"
    - "at low snr asymmetric quantizers are better"
    - "multiple parameter estimation with quantized channel output"
    - "increased capacity per unit cost by oversampling"

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)