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: "user scheduling for millimeter wave hybrid beamforming systems with low resolution adcs"
  Abstract: We investigate uplink user scheduling for millimeter wave (mmWave) hybrid analog/digital beamforming systems with low-resolution analog-to-digital converters (ADCs). Deriving new scheduling criteria for the mmWave systems, we show that the channel structure in the beamspace, in addition to the channel magnitude and orthogonality, plays a key role in maximizing the achievable rates of scheduled users due to quantization error. The criteria show that to maximize the achievable rate regarding the channel structure, the channels of the scheduled users need to have (1) as many propagation paths as possible with unique angle-of-arrivals (AoAs) and (2) even power distribution in the beamspace. Leveraging the derived criteria, we propose an efficient scheduling algorithm for mmWave zero-forcing receivers with low-resolution ADCs. We further propose a chordal distance-based scheduling algorithm that exploits only the AoA knowledge and analyze the performance of the algorithm by deriving ergodic rates in closed form. Based on the derived rates, we show that the beamspace channel leakage resulting from phase offsets between AoAs and quantized angles of analog combiners can achieve sum rate gain by reducing quantization error compared to the channel without leakage. Simulation results validate the sum rate performance of the proposed algorithms and derived ergodic rates expressions.

Connected through hyperedge HE-1 (induced by source paper "two stage analog combining in hybrid beamforming systems with low resolution adcs"):
  with members:
    - "a comparison of hybrid beamforming and digital beamforming with low resolution adcs for multiple users and imperfect csi"
    - "resolution adaptive hybrid mimo architectures for millimeter wave communications"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"
    - "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"

Connected through hyperedge HE-2 (induced by source paper "a hybrid beamforming receiver with two stage analog combining and low resolution adcs"):
  with members:
    - "a comparison of hybrid beamforming and digital beamforming with low resolution adcs for multiple users and imperfect csi"
    - "resolution adaptive hybrid mimo architectures for millimeter wave communications"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"
    - "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "hybrid mimo architectures for millimeter wave communications phase shifters or switches"

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)