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: "on the temporal effects of mobile blockers in urban millimeter wave cellular scenarios"
  Abstract: Millimeter-wave (mmWave) propagation is known to be severely affected by the blockage of the line-of-sight (LoS) path. In contrast to microwave systems, at shorter mmWave wavelengths such blockage can be caused by human bodies, where their mobility within environment makes wireless channel alternate between the blocked and non-blocked LoS states. Following the recent 3GPP requirements on modeling the dynamic blockage as well as the temporal consistency of the channel at mmWave frequencies, in this paper a new model for predicting the state of a user in the presence of mobile blockers for representative 3GPP scenarios is developed: urban micro cell (UMi) street canyon and park/stadium/square. It is demonstrated that the blockage effects produce an alternating renewal process with exponentially distributed non-blocked intervals, and blocked durations that follow the general distribution. The following metrics are derived (i) the mean and the fraction of time spent in blocked/non-blocked state, (ii) the residual blocked/non-blocked time, and (iii) the time-dependent conditional probability of having blockage/no blockage at time t1 given that there was blockage/no blockage at time t0. The latter is a function of the arrival rate (intensity), width, and height of moving blockers, distance to the mmWave access point (AP), as well as the heights of the AP and the user device. The proposed model can be used for system-level characterization of mmWave cellular communication systems. For example, the optimal height and the maximum coverage radius of the mmWave APs are derived, while satisfying the required mean data rate constraint. The system-level simulations corroborate that the use of the proposed method considerably reduces the modeling complexity.

Connected through hyperedge HE-1 (induced by source paper "an accurate approximation of resource request distributions in millimeter wave 3gpp new radio systems"):
  with members:
    - "analysis of human body blockage in urban millimeter wave cellular communications"

Connected through hyperedge HE-2 (induced by source paper "energy efficient interactive beam alignment for millimeter wave networks"):
  with members:
    - "coded energy efficient beam alignment for millimeter wave networks"
    - "optimal beam sweeping and communication in mobile millimeter wave networks"
    - "throughput optimal beam alignment in millimeter wave networks"
    - "inverse multipath fingerprinting for millimeter wave v2i beam alignment"
    - "compressive channel estimation and tracking for large arrays in mm wave picocells"
    - "design and analysis of initial access in millimeter wave cellular networks"
    - "beamforming tradeoffs for initial ue discovery in millimeter wave mimo systems"
    - "the impact of beamwidth on temporal channel variation in vehicular channels and its implications"

Connected through hyperedge HE-3 (induced by source paper "maximum throughput scheduling for multi connectivity in millimeter wave networks"):
  with members:
    - "initial access in 5g mmwave cellular networks"
    - "optimal cell clustering and activation for energy saving in load coupled wireless networks"
    - "the transitional behavior of interference in millimeter wave networks and its impact on medium access control"

Connected through hyperedge HE-4 (induced by source paper "caching aided collaborative d2d operation for predictive data dissemination in industrial iot"):
  with members:
    - "caching at the wireless edge design aspects challenges and future directions"
    - "hybrid millimeter wave systems a novel paradigm for hetnets"
    - "living on the edge the role of proactive caching in 5g wireless 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)