human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"):
  Abstract: The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, are natural candidates to provide the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

Includes members:
  Member "properties of an aloha like stability region":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the aloha throughput fairness tradeoff")
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "m2m massive access in lte rach performance evaluation in a smart city scenario":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a thorough study of lorawan performance under different parameter settings")
  Member "on the evaluation of lte random access channel overload in a smart city scenario":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spatiotemporal model for uplink iot traffic scheduling random access paradox")
  Member "analytical modeling of interference aware power control for the uplink of heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a spatiotemporal model for peak aoi in uplink iot networks time vs event triggered traffic")
  Member "modeling cellular networks in fading environments with dominant specular components":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks")
  Member "tractable stochastic geometry model for iot access in lte networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic binary countdown for massive iot random access in dense 5g networks")
  Member "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")

Question: Please tell me which class the source paper 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.IT(Information Theory)