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: "narrowband channel estimation for hybrid beamforming millimeter wave communication systems with one bit quantization"
  Abstract: Millimeter wave (mmWave) spectrum has drawn attention due to its tremendous available bandwidth. The high propagation losses in the mmWave bands necessitate beamforming with a large number of antennas. Traditionally each antenna is paired with a high-speed analog-to-digital converter (ADC), which results in high power consumption. A hybrid beamforming architecture and one-bit resolution ADCs have been proposed to reduce power consumption. However, analog beamforming and one-bit quantization make channel estimation more challenging. In this paper, we propose a narrowband channel estimation algorithm for mmWave communication systems with one-bit ADCs and hybrid beamforming based on generalized approximate message passing (GAMP). We show through simulation that 1) GAMP variants with one-bit ADCs have better performance than do least-squares estimation methods without quantization, 2) the proposed one-bit GAMP algorithm achieves the lowest estimation error among the GAMP variants, and 3) exploiting more frames and RF chains enhances the channel estimation performance.

Connected through hyperedge HE-1 (induced by source paper "user scheduling for millimeter wave hybrid beamforming systems with low resolution adcs"):
  with members:
    - "cellular connected uav potentials challenges and promising technologies"
    - "spatial channel covariance estimation for the hybrid mimo architecture a compressive sensing based approach"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "user scheduling for millimeter wave mimo communications with low resolution adcs"
    - "resolution adaptive hybrid mimo architectures for millimeter wave communications"
    - "adc bit optimization for spectrum and energy efficient millimeter wave communications"
    - "codebook based hybrid precoding for millimeter wave multiuser systems"

Connected through hyperedge HE-2 (induced by source paper "hardware limited task based quantization"):
  with members:
    - "analog to digital compression a new paradigm for converting signals to bits"
    - "performance analysis for channel estimation with 1 bit adc and unknown quantization threshold"
    - "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"
    - "fundamental distortion limits of analog to digital compression"
    - "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs"

Connected through hyperedge HE-3 (induced by source paper "user scheduling for millimeter wave mimo communications with low resolution adcs"):
  with members:
    - "resolution adaptive hybrid mimo architectures for millimeter wave communications"
    - "adc bit allocation under a power constraint for mmwave massive mimo communication receivers"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "what will 5g be"
    - "spatially sparse precoding in millimeter wave mimo systems"

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)