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: "hardware limited task based quantization"
  Abstract: Quantization plays a critical role in digital signal processing systems. Quantizers are typically designed to obtain an accurate digital representation of the input signal, operating independently of the system task, and are commonly implemented using serial scalar analog-to-digital converters (ADCs). In this work, we study hardware-limited task-based quantization, where a system utilizing a serial scalar ADC is designed to provide a suitable representation in order to allow the recovery of a parameter vector underlying the input signal. We propose hardware-limited task-based quantization systems for a fixed and finite quantization resolution, and characterize their achievable distortion. We then apply the analysis to the practical setups of channel estimation and eigen-spectrum recovery from quantized measurements. Our results illustrate that properly designed hardware-limited systems can approach the optimal performance achievable with vector quantizers, and that by taking the underlying task into account, the quantization error can be made negligible with a relatively small number of bits.

Connected through hyperedge HE-1 (induced by source paper "task based quantization with application to mimo receivers"):
  with members:
    - "dynamic metasurface antennas for mimo ofdm receivers with bit limited adcs"
    - "dynamic metasurface antennas for uplink massive mimo systems"
    - "on the spectral efficiency of noncooperative uplink massive mimo systems"
    - "spectral efficiency of mixed adc massive mimo"
    - "soft to hard vector quantization for end to end learning compressible representations"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "principal inertia components and applications"

Connected through hyperedge HE-2 (induced by source paper "serial quantization for representing sparse signals"):
  with members:
    - "learning distributions from their samples under communication constraints"
    - "efficient data collection over multiple access wireless sensors network"
    - "quantization of compressive samples with stable and robust recovery"
    - "quantization and compressive sensing"
    - "spatial compressive sensing for mimo radar"
    - "group testing algorithms bounds and simulations"
    - "quantized iterative hard thresholding bridging 1 bit and high resolution quantized compressed sensing"
    - "gespar efficient phase retrieval of sparse signals"

Connected through hyperedge HE-3 (induced by source paper "dynamic metasurface antennas for uplink massive mimo systems"):
  with members:
    - "on the spectral efficiency of noncooperative uplink massive mimo systems"
    - "measurement matrix design for phase retrieval based on mutual information"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "resolution adaptive hybrid mimo architectures for millimeter wave communications"
    - "hybrid analog digital beamforming for massive mimo systems"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"
    - "mixed adc massive mimo detectors performance analysis and design optimization"

Connected through hyperedge HE-4 (induced by source paper "dynamic metasurface antennas for mimo ofdm receivers with bit limited adcs"):
  with members:
    - "reliable ofdm receiver with ultra low resolution adc"
    - "dynamic metasurface antennas for uplink massive mimo systems"
    - "on the spectral efficiency of noncooperative uplink massive mimo systems"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "a comparison of hybrid beamforming and digital beamforming with low resolution adcs for multiple users and imperfect csi"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "hybrid analog and digital beamforming for mmwave ofdm large scale antenna arrays"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"

Connected through hyperedge HE-5 (induced by source paper "comparison limited vector quantization"):
  with members:
    - "on mimo channel capacity with output quantization constraints"

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)