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: "spatial birth death wireless networks"
  Abstract: We propose and study a novel continuous space-time model for wireless networks, which considers the stochastic interactions in both space through interference and in time due to randomness in traffic. Our model consists of an interacting particle birth–death dynamics incorporating information-theoretic spectrum-sharing. Roughly speaking, particles (or more generally wireless links) arrive according to a Poisson point process on space-time, and stay for a duration governed by the local configuration of points present, and then exit the network after completion of a file transfer. We analyze this particle dynamics to derive an explicit condition for time ergodicity (i.e., stability), which is tight. We also prove that when the dynamics is ergodic, the steady-state point process of links (or particles) exhibits a form statistical  clustering . Based on the clustering, we propose a conjecture, which we leverage to derive approximations, bounds, and asymptotics on performance characteristics, such as delay and mean number of links per unit-space in the stationary regime. The mathematical analysis is combined with discrete event simulation to study the performance of this type of networks.

Connected through hyperedge HE-1 (induced by source paper "stability and metastability of traffic dynamics in uplink random access networks"):
  with members:
    - "self organized scheduling request for uplink 5g networks a d2d clustering approach"
    - "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "performance laws of large heterogeneous cellular networks"
    - "can p2p networks be super scalable"
    - "a tractable approach to coverage and rate in cellular networks"
    - "asymptotic stability region of slotted aloha"

Connected through hyperedge HE-2 (induced by source paper "stability conditions for a decentralised medium access algorithm single and multi hop networks"):
  with members:
    - "stability conditions for a discrete time decentralised medium access algorithm"

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)