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: "a primer on 3gpp narrowband internet of things nb iot"
  Abstract: Narrowband Internet of Things (NB-IoT) is a new cellular technology introduced in 3GPP Release 13 for providing wide-area coverage for the Internet of Things (IoT). This article provides an overview of the air interface of NB-IoT. We describe how NB-IoT addresses key IoT requirements such as deployment flexibility, low device complexity, long battery life time, support of massive number of devices in a cell, and significant coverage extension beyond existing cellular technologies. We also share the various design rationales during the standardization of NB-IoT in Release 13 and point out several open areas for future evolution of NB-IoT.

Connected through hyperedge HE-1 (induced by source paper "contextual bandit learning for machine type communications in the null space of multi antenna systems"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "sleeping multi armed bandit learning for fast uplink grant allocation in machine type communications"
    - "a directed information learning framework for event driven m2m traffic prediction"
    - "fast uplink grant for machine type communications challenges and opportunities"
    - "deep learning for signal authentication and security in massive internet of things systems"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "random access schemes in wireless systems with correlated user activity"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"

Connected through hyperedge HE-2 (induced by source paper "nb iot uplink receiver design and performance study"):
  with members:
    - "random access preamble design and detection for 3gpp narrowband iot systems"

Connected through hyperedge HE-3 (induced by source paper "deep reinforcement learning based modulation and coding scheme selection in cognitive heterogeneous networks"):
  with members:
    - "cooperative ambient backscatter communications for green internet of things"
    - "intelligent power control for spectrum sharing in cognitive radios a deep reinforcement learning approach"
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "spectrum access in cognitive radio using a two stage reinforcement learning approach"
    - "spectrum sharing for internet of things a survey"
    - "a reinforcement learning approach to proactive caching in wireless networks"
    - "deep reinforcement learning multiple access for heterogeneous wireless networks"

Connected through hyperedge HE-4 (induced by source paper "deep reinforcement learning for real time optimization in nb iot networks"):
  with members:
    - "polynomial regression as an alternative to neural nets"
    - "latency energy tradeoff based on channel scheduling and repetitions in nb iot systems"
    - "random access preamble design and detection for 3gpp narrowband iot systems"
    - "wide area wireless communication challenges for the internet of things"
    - "value function approximations for partially observable markov decision processes"

Connected through hyperedge HE-5 (induced by source paper "cooperative deep reinforcement learning for multiple group nb iot networks optimization"):
  with members:
    - "latency energy tradeoff based on channel scheduling and repetitions in nb iot systems"
    - "random access preamble design and detection for 3gpp narrowband iot systems"
    - "deep reinforcement learning with double q learning"

Connected through hyperedge HE-6 (induced by source paper "spectrum sharing for internet of things a survey"):
  with members:
    - "riding on the primary a new spectrum sharing paradigm for wireless powered iot devices"
    - "modulation in the air backscatter communication over ambient ofdm carrier"
    - "efficient scheduling and power allocation for d2d assisted wireless caching networks"

Connected through hyperedge HE-7 (induced by source paper "opportunistic scheduling of machine type communications as underlay to cellular networks"):
  with members:
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "fundamentals of throughput maximization with random arrivals for m2m communications"
    - "opportunistic interference alignment for mimo interfering multiple access channels"
    - "improving macrocell small cell coexistence through adaptive interference draining"
    - "from spectrum pooling to space pooling opportunistic interference alignment in mimo cognitive networks"
    - "opportunistic spatial orthogonalization and its application in fading cognitive radio networks"

Connected through hyperedge HE-8 (induced by source paper "realization of cdma based iot services with shared band operation of lte in 5g"):
  with members:
    - "demo abstract cdma based iot services with shared band operation of lte in 5g"
    - "coordinated dynamic spectrum management of lte u and wi fi 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)