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: "random access analysis for massive iot networks under a new spatio temporal model a stochastic geometry approach"
  Abstract: Massive Internet of Things (mIoT) has provided an auspicious opportunity to build powerful and ubiquitous connections that faces a plethora of new challenges, where cellular networks are potential solutions due to their high scalability, reliability, and efficiency. The Random Access CHannel (RACH) procedure is the first step of connection establishment between IoT devices and Base Stations (BSs) in the cellular-based mIoT network, where modelling the interactions between static properties of physical layer network and dynamic properties of queue evolving in each IoT device are challenging. To tackle this, we provide a novel traffic-aware spatio-temporal model to analyze RACH in cellular-based mIoT networks, where the physical layer network is modelled and analyzed based on stochastic geometry in the spatial domain, and the queue evolution is analyzed based on probability theory in the time domain. For performance evaluation, we derive the exact expressions for the preamble transmission success probabilities of a randomly chosen IoT device with different RACH schemes in each time slot, which offer insights into effectiveness of each RACH scheme. Our derived analytical results are verified by the realistic simulations capturing the evolution of packets in each IoT device. This mathematical model and analytical framework can be applied to evaluate the performance of other types of RACH schemes in the cellular-based networks by simply integrating its preamble transmission principle.

Connected through hyperedge HE-1 (induced by source paper "spatio temporal modeling for massive and sporadic access"):
  with members:
    - "tradeoff between delay and physical layer security in wireless networks"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "massive machine type communication with data aggregation and resource scheduling"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "user centric mobility management in ultra dense cellular networks under spatio temporal dynamics"
    - "spatial spectrum and energy efficiency of random cellular networks"

Connected through hyperedge HE-2 (induced by source paper "ran slicing for massive iot and bursty urllc service multiplexing analysis and optimization"):
  with members:
    - "how should i orchestrate resources of my slices for bursty urllc service provision"
    - "resource allocation and harq optimization for urllc traffic in 5g wireless networks"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "stochastic coalitional games for cooperative random access in m2m communications"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"
    - "downlink capacity and base station density in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "effect of spatial and temporal traffic statistics on the performance of wireless networks"):
  with members:
    - "tradeoff between delay and physical layer security in wireless networks"
    - "the meta distribution of the sir for cellular networks with power control"
    - "stable throughput and delay analysis of a random access network with queue aware transmission"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "poisson cluster process based analysis of hetnets with correlated user and base station locations"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "the learning and prediction of application level traffic data in cellular networks"
    - "user centric mobility management in ultra dense cellular networks under spatio temporal dynamics"

Connected through hyperedge HE-4 (induced by source paper "spatiotemporal model for uplink iot traffic scheduling random access paradox"):
  with members:
    - "tradeoff between delay and physical layer security in wireless networks"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "the meta distribution of the sir for cellular networks with power control"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "lte lte a random access for massive machine type communications in smart cities"
    - "on the evaluation of lte random access channel overload in a smart city scenario"
    - "toward a tractable delay analysis in ultra dense networks"
    - "analytical modeling of interference aware power control for the uplink of heterogeneous cellular networks"

Connected through hyperedge HE-5 (induced by source paper "energy sustainable iot with individual qos constraints through miso swipt multicasting"):
  with members:
    - "jointly optimal spatial channel assignment and power allocation for mimo swipt systems"
    - "robust an aided beamforming and power splitting design for secure miso cognitive radio with swipt"
    - "power allocation and scheduling for swipt systems with non linear energy harvesting model"
    - "joint beamforming design for multi user wireless information and power transfer"
    - "multiuser miso beamforming for simultaneous wireless information and power transfer"
    - "joint transmit beamforming and receive power splitting for miso swipt systems"
    - "beamforming for miso interference channels with qos and rf energy transfer"
    - "robust beamforming for wireless information and power transmission"

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.IT(Information Theory)