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: "elevation beamforming with full dimension mimo architectures in 5g systems a tutorial"
  Abstract: Full dimension (FD) multiple-input multiple-output (MIMO) technology has attracted substantial research attention from both wireless industry and academia in the last few years as a promising technique for next-generation wireless communication networks. FD-MIMO scenarios utilize a planar two-dimensional (2D) active antenna system (AAS) that not only allows a large number of antenna elements to be placed within feasible base station (BS) form factors, but also provides the ability of adaptive electronic beam control over both the elevation and the traditional azimuth dimensions. This paper presents a tutorial on elevation beamforming analysis for cellular networks utilizing FD massive MIMO antenna arrays. In contrast to existing works that focus on the standardization of FD-MIMO in the 3rd Generation Partnership Project (3GPP), this tutorial is distinguished by its depth with respect to the theoretical aspects of antenna array and 3D channel modeling. In an attempt to bridge the gap between industry and academia, this preliminary tutorial introduces the relevant array and transceiver architecture designs proposed in the 3GPP Release 13 that enable elevation beamforming. Then it presents and compares two different 3D channel modeling approaches that can be utilized for the performance analysis of elevation beamforming techniques. The spatial correlation in FD-MIMO arrays is characterized and compared based on both channel modeling approaches and some insights into the impact of different channel and array parameters on the correlation are drawn. All these aspects are put together to provide a mathematical framework for the design of elevation beamforming schemes in single-cell and multi-cell scenarios. Simulation examples associated with comparisons and discussions are also presented.

Connected through hyperedge HE-1 (induced by source paper "3d beamforming in reconfigurable intelligent surfaces assisted wireless communication networks"):
  with members:
    - "resource allocation for secure irs assisted multiuser miso systems"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "large intelligent surface assisted wireless communication exploiting statistical csi"
    - "joint tilt angle adaptation and beamforming in multicell multiuser cellular networks"

Connected through hyperedge HE-2 (induced by source paper "from a human centric perspective what might 6g be"):
  with members:
    - "towards 6g networks use cases and technologies"
    - "capacity and coverage enhancement using long endurance tethered airborne base stations"
    - "enabling smart buildings by indoor visible light communications and machine learning"
    - "a key 6g challenge and opportunity connecting the remaining 4 billions a survey on rural connectivity"
    - "6g the next frontier"
    - "evolution of physical layer communications research in the post 5g era"
    - "ultrareliable and low latency communication techniques for tactile internet services"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"

Connected through hyperedge HE-3 (induced by source paper "3d beamforming based dynamic tdd interference mitigation scheme"):
  with members:
    - "a 3d beamforming scheme based on the spatial distribution of user locations"
    - "interference analysis in dynamic tdd system combined or not with cell clustering scheme"
    - "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"
    - "analytical tractability of hexagonal network model with random user location"

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)