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: "tractable resource management in millimeter wave overlaid ultra dense cellular networks"
  Abstract: What does millimeter-wave (mmW) seek assistance for from micro-wave ({\mu}W) in a mmW overlaid 5G cellular network? This paper raises the question of whether to complement downlink (DL) or uplink (UL) transmissions, and concludes that {\mu}W should aid UL more. Such dedication to UL results from the low mmW UL rate due to high peak-to-average power ratio (PAPR) at mobile users. The DL/UL allocations are tractably provided based on a novel closed-form mm-{\mu}W spectral efficiency (SE) derivation via stochastic geometry. The findings explicitly indicate: (i) both DL/UL mmW (or {\mu}W) SEs coincidentally converge on the same value in an ultra-dense cellular network (UDN) and (ii) such a mmW (or {\mu}W) UDN SE is a logarithmic function of BS-to-user density ratio. The corresponding mm-{\mu}W resource management is evaluated by utilizing a three dimensional (3D) blockage model with real geography in Seoul, Korea.

Connected through hyperedge HE-1 (induced by source paper "tractable resource management with uplink decoupled millimeter wave overlay in ultra dense cellular networks"):
  with members:
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "why to decouple the uplink and downlink in cellular networks and how to do it"
    - "resource management and cell planning in millimeter wave overlaid ultra dense cellular networks"
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
    - "effect of los nlos propagation on ultra dense networks"
    - "are we approaching the fundamental limits of wireless network densification"
    - "downlink cellular network analysis with multi slope path loss models"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"

Connected through hyperedge HE-2 (induced by source paper "user centric mobility management in ultra dense cellular networks under spatio temporal dynamics"):
  with members:
    - "tractable resource management with uplink decoupled millimeter wave overlay in ultra dense cellular networks"
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
    - "stochastic differential games and energy efficient power control"
    - "adaptive training for correlated fading channels with feedback"

Connected through hyperedge HE-3 (induced by source paper "the transitional behavior of interference in millimeter wave networks and its impact on medium access control"):
  with members:
    - "on the accuracy of interference models in wireless communications"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "millimeter wave ad hoc networks noise limited or interference limited"
    - "beam searching and transmission scheduling in millimeter wave communications"
    - "millimeter wave cellular networks a mac layer perspective"
    - "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"
    - "on the joint impact of beamwidth and orientation error on throughput in directional wireless poisson networks"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"

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)