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: "large scale antenna operation in heterogeneous cloud radio access networks a partial centralization approach"
  Abstract: To satisfy the ever increasing capacity demand and quality of service requirements of users, 5G cellular systems will take the form of HetNets that consist of macrocells and small cells. To build and operate such systems, mobile operators have given significant attention to cloud radio access networks, C-RANs, due to their beneficial features of performance optimization and cost effectiveness. Along with the architectural enhancement of C-RAN, largescale antennas (a.k.a. massive MIMO) at cell sites contribute greatly to increased network capacity either with higher spectral efficiency or through permitting many users at once. In this article, we discuss the challenging issues of CRAN- based HetNets (H-CRAN), especially with respect to large-scale antenna operation. We provide an overview of existing C-RAN architectures in terms of large-scale antenna operation and promote a partially centralized approach. This approach remarkably reduces fronthaul overheads in C-RANs with large-scale antennas. We also provide some insights into its potential and applicability in the fronthaul bandwidth-limited H-CRAN with large-scale antennas.

Connected through hyperedge HE-1 (induced by source paper "boosting fronthaul capacity global optimization of power sharing for centralized radio access network"):
  with members:
    - "differential evolution algorithm aided turbo channel estimation and multi user detection for g fast systems in the presence of fext"
    - "regularized zero forcing precoding aided adaptive coding and modulation for large scale antenna array based air to air communications"
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "joint user selection and energy minimization for ultra dense multi channel c ran with incomplete csi"
    - "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"
    - "adaptive coding and modulation for large scale antenna array based aeronautical communications in the presence of co channel interference"
    - "multivariate fronthaul quantization for downlink c ran"
    - "fronthauling for 5g lte u ultra dense cloud small cell networks"

Connected through hyperedge HE-2 (induced by source paper "complexity aware scheduling for an ldpc encoded c ran uplink"):
  with members:
    - "analysis of a frequency hopping millimeter wave cellular uplink"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "the complexity rate tradeoff of centralized radio access networks"
    - "computationally aware sum rate optimal scheduling for centralized radio access networks"
    - "the role of computational outage in dense cloud based centralized radio access networks"
    - "five disruptive technology directions for 5g"

Connected through hyperedge HE-3 (induced by source paper "recent advances in cloud radio access networks system architectures key techniques and open issues"):
  with members:
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"
    - "optimal fronthaul quantization for cloud radio positioning"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "contract based interference coordination in heterogeneous cloud radio access networks"
    - "are heterogeneous cloud based radio access networks cost effective"
    - "energy efficient resource assignment and power allocation in heterogeneous cloud radio access networks"
    - "cooperative interference mitigation and handover management for heterogeneous cloud small cell networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"

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.NI(Networking and Internet Architecture)