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: "doa parameter estimation with 1 bit quantization bounds methods and the exponential replacement"
  Abstract: While 1-bit analog-to-digital conversion (ADC) allows to significantly reduce the analog complexity of wireless receive systems, using the exact likelihood function of the hard-limiting system model in order to obtain efficient algorithms in the digital domain can make 1-bit signal processing challenging. If the signal model before the quantizer consists of correlated Gaussian random variables, the tail probability for a multivariate Gaussian distribution with N dimensions (general orthant probability) is required in order to formulate the likelihood function of the quantizer output. As a closed-form expression for the general orthant probability is an open mathematical problem, formulation of efficient processing methods for correlated and quantized data and an analytical performance assessment have, despite their high practical relevance, only found limited attention in the literature on quantized estimation theory. Here we review the approach of replacing the original system model by an equivalent distribution within the exponential family. For 1-bit signal processing, this allows to circumvent calculation of the general orthant probability and gives access to a conservative approximation of the receive likelihood. For the application of blind direction-of-arrival (DOA) parameter estimation with an array of K sensors, each performing 1-bit quantization, we demonstrate how the exponential replacement enables to formulate a pessimistic version of the Cram\'er-Rao lower bound (CRLB) and to derive an asymptotically achieving conservative maximum-likelihood estimator (CMLE). The 1-bit DOA performance analysis based on the pessimistic CRLB points out that a low-complexity radio front-end design with 1-bit ADC is in particular suitable for blind wireless DOA estimation with a large number of array elements operating in the medium SNR regime.

Connected through hyperedge HE-1 (induced by source paper "sensitivity analysis for binary sampling systems via quantitative fisher information lower bounds"):
  with members:
    - "a pessimistic approximation for the fisher information measure"
    - "measurement driven quality assessment of nonlinear systems by exponential replacement"
    - "a lower bound for the fisher information measure"
    - "gaussian assumption the least favorable but the most useful lecture notes"
    - "a general framework for transmission with transceiver distortion and some applications"
    - "information theoretic proofs of entropy power inequalities"
    - "multiple parameter estimation with quantized channel output"

Connected through hyperedge HE-2 (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"
    - "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"
    - "a general framework for transmission with transceiver distortion and some applications"

Connected through hyperedge HE-3 (induced by source paper "dominant channel estimation via mips for large scale antenna systems with one bit adcs"):
  with members:
    - "quantization design and channel estimation for massive mimo systems with one bit adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "massive mimo ten myths and one critical question"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "massive mimo for next generation wireless systems"
    - "massive mimo with 1 bit adc"

Connected through hyperedge HE-4 (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"
    - "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"
    - "overdemodulation for high performance receivers with low resolution adc"

Connected through hyperedge HE-5 (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"
    - "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"
    - "overdemodulation for high performance receivers with low resolution adc"
    - "multiple parameter estimation with quantized channel output"
    - "increased capacity per unit cost by oversampling"

Connected through hyperedge HE-6 (induced by source paper "asymptotic signal detection rates with 1 bit array measurements"):
  with members:
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "double detector for sparse signal detection from one bit compressed sensing measurements"
    - "low power wideband sensing for one bit quantized cognitive radio systems"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "one bit decentralized detection with a rao test for multisensor fusion"

Connected through hyperedge HE-7 (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"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "a lower bound for the fisher information measure"
    - "overdemodulation for high performance receivers with low resolution adc"
    - "gaussian assumption the least favorable but the most useful lecture notes"

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)