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: "promises and caveats of uplink iot ultra dense networks"
  Abstract: In this paper, by means of simulations, we evaluate the uplink (UL) performance of an Internet of Things (IoT) capable ultra-dense network (UDN) in terms of the coverage probability and the density of reliably working user equipments (UEs). From our study, we show the benefits and challenges that UL IoT UDNs will bring about in the future. In more detail, for a low-reliability criterion, such as achieving a UL signal-to-interference-plus-noise ratio (SINR) above 0 dB, the density of reliably working UEs grows quickly with the network densification, showing the potential of UL IoT UDNs. In contrast, for a high-reliability criterion, such as achieving a UL SINR above 10 dB, the density of reliably working UEs remains to be low in UDNs due to excessive inter-cell interference, which should be considered when operating UL IoT UDNs. Moreover, considering the existence of a non-zero antenna height difference between base stations (BSs) and UEs, the density of reliably working UEs could even decrease as we deploy more BSs. This calls for the usage of sophisticated interference management schemes and/or beam steering/shaping technologies in UL IoT UDNs.

Connected through hyperedge HE-1 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"):
  with members:
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "supporting uav cellular communications through massive mimo"
    - "uav aided offloading for cellular hotspot"
    - "the essential guide to realizing 5g connected uavs with massive mimo"
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "optimal base station antenna downtilt in downlink 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)