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: "integrated access and backhaul in 5g mmwave networks potentials and challenges"
  Abstract: Integrated Access and Backhaul (IAB) is being investigated as a means to overcome deployment costs of ultra-dense 5G millimeter wave (mmWave) networks by realizing wireless backhaul links to relay the access traffic. For the development of these systems, however, it is fundamental to validate the performance of IAB in realistic scenarios through end-to-end system level simulations. In this paper, we shed light on the most recent standardization activities on IAB, and compare architectures with and without IAB in mmWave deployments. While it is well understood that IAB networks reduce deployment costs by obviating the need to provide wired backhaul to each cellular base-station, in this paper we demonstrate the cell-edge throughput advantage offered by IAB using end-to-end system level simulations. We further highlight some research challenges associated with this architecture that will require further investigations.

Connected through hyperedge HE-1 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights"):
  with members:
    - "a tractable analysis of the blind spot probability in localization networks under correlated blocking"
    - "end to end simulation of integrated access and backhaul at mmwaves"
    - "max min rates in self backhauled millimeter wave cellular networks"
    - "distributed path selection strategies for integrated access and backhaul at mmwaves"
    - "modeling and analyzing millimeter wave cellular systems"
    - "integrated mmwave access and backhaul in 5g bandwidth partitioning and downlink analysis"
    - "capacity scaling of cellular networks impact of bandwidth infrastructure density and number of antennas"
    - "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"

Connected through hyperedge HE-2 (induced by source paper "optimal link scheduling in millimeter wave multi hop networks with mu mimo radios"):
  with members:
    - "distributed path selection strategies for integrated access and backhaul at mmwaves"
    - "hierarchical codebook design for beamforming training in millimeter wave communication"
    - "understanding noise and interference regimes in 5g millimeter wave cellular networks"
    - "codebook design for millimeter wave channel estimation with hybrid precoding structure"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"
    - "towards an appropriate receiver beamforming scheme for millimeter wave communication a power consumption based comparison"
    - "massive mimo ten myths and one critical question"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"

Connected through hyperedge HE-3 (induced by source paper "non terrestrial communication in the 6g era challenges and opportunities"):
  with members:
    - "towards 6g networks use cases and technologies"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "optical communication in space challenges and mitigation techniques"

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)