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: "secure hybrid analog and digital receive beamforming schemes for efficient interference reduction"
  Abstract: In spatial spectrum estimation field, medium-scale or large-scale receive antenna array with digital beamforming can be employed at receiver to achieve a high-resolution direction of arrival (DOA) estimation and make a significant interference suppression, but leads to an expensive RF-chain circuit cost. Thus, a robust hybrid analog-and-digital beamforming (ADB) structure is proposed to greatly reduces the number of RF-chains so that the cost of RF-chains is lowered significantly. This ADB structure at receiver is to attenuate the jamming signals from undesired directions and boost the receive quality of the desired signal for the purpose of secure receiving. In this paper, we first propose a hybrid ADB scheme with analytic expression, which consists of null space projection in analog beamforming part and diagonal loading method in digital beamforming part. Then, by exploiting DOA estimation errors, we construct a robust hybrid beamforming algorithm using the conditional expectation of DOA instead of making direct use of the estimated DOA. Simulation result shows that the proposed robust beamforming scheme performs more robust and makes a more efficient reduction in jamming interference to improve the receive signal to interference and noise ratio compared to non-burst ADB scheme proposed by us.

Connected through hyperedge HE-1 (induced by source paper "robust hybrid precoding for beam misalignment in millimeter wave communications"):
  with members:
    - "impact of beam misalignment on hybrid beamforming noma for mmwave communications"
    - "joint power allocation and beamforming for non orthogonal multiple access noma in 5g millimeter wave communications"
    - "alternating minimization for hybrid precoding in multiuser ofdm mmwave systems"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "analysis on 60 ghz wireless communications with beamwidth dependent misalignment"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "massive mimo combining with switches"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"

Connected through hyperedge HE-2 (induced by source paper "secure hybrid digital and analog precoder for mmwave systems with low resolution dacs and finite quantized phase shifters"):
  with members:
    - "energy efficiency of mmwave massive mimo precoding with low resolution dacs"
    - "hybrid analog and digital beamforming for mmwave ofdm large scale antenna arrays"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "an overview of sustainable green 5g networks"
    - "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs"
    - "dynamic subarrays for hybrid precoding in wideband mmwave mimo systems"
    - "achievable rate and energy efficiency of hybrid and digital beamforming receivers with low resolution adc"

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)