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: "interference analysis in dynamic tdd system combined or not with cell clustering scheme"
  Abstract: Dynamic Time Division Duplex (TDD) has been introduced as a solution to deal with the uplink and downlink traffic asymmetry, mainly observed for dense heterogeneous network deployments. However, the use of this feature requires new interference mitigation schemes capable to handle two additional types of interferences between cells in opposite transmission cycle: downlink to uplink and uplink to downlink interferences. Among them, Cell clustering has been proposed as an efficient solution to minimize inter-cell interferences in opposite transmission directions and somehow responds to the requirements of enhanced Interference Mitigation and Traffic Adaptation (eIMTA) problem. This work is devoted to provide a new analytical approach to model inter-cell interferences and quantify performances of Dynamic TDD system in terms of SINR (Signal to Interferences plus Noise Ratio) distribution. Analytical system performance investigation concerns two scenarios: i) basic Dynamic TDD without any other feature and ii) Dynamic TDD with interference mitigation schemes.

Connected through hyperedge HE-1 (induced by source paper "dynamic tdd interference analysis in macro cell and small cell deployments"):
  with members:
    - "3d beamforming based dynamic tdd interference mitigation scheme"
    - "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"
    - "a primer on cellular network analysis using stochastic geometry"
    - "analytical tractability of hexagonal network model with random user location"
    - "d2d enhanced heterogeneous cellular networks with dynamic tdd"
    - "dynamic uplink downlink optimization in tdd based small cell networks"
    - "analytical modeling of uplink cellular networks"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"

Connected through hyperedge HE-2 (induced by source paper "a 3d beamforming scheme based on the spatial distribution of user locations"):
  with members:
    - "optimal base station antenna downtilt in downlink cellular networks"
    - "analytical tractability of hexagonal network model with random user location"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "a tractable approach to coverage and rate in cellular networks"

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"
    - "elevation beamforming with full dimension mimo architectures in 5g systems a tutorial"
    - "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.NI(Networking and Internet Architecture)