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: "effective capacity analysis in ultra dense wireless networks with random interference"
  Abstract: Ultra-dense networks (UDNs) provide a promising paradigm to cope with exponentially increasing mobile traffic. However, little work has to date considered unsaturated traffic with quality-of-service (QoS) requirements. This paper presents a new cross-layer analytical model to capture the unsaturated traffic of a UDN in the presence of QoS requirements. The effective capacity (EC) of the UDN is derived, taking into account small-scale channel fading and possible interference. Key properties of the EC are revealed. The amount of traffic impacts effective capacity of the UDN due to the sophisticated interactions among small base stations operating in the same frequency. The maximization of total effective capacity is formulated as a non-cooperative game in the paper. The best-response function is derived, iteratively searching the Nash equilibrium point. System simulation results indicate that our proposed model is accurate. The simulations also show the maximum allowed arrival rate with the QoS guarantee, compared with the full interference model.

Connected through hyperedge HE-1 (induced by source paper "game theoretic optimization for machine type communications under qos guarantee"):
  with members:
    - "effective capacity of licensed assisted access in unlicensed spectrum for 5g from theory to application"
    - "on the reliability of lte random access performance bounds for machine to machine burst resolution time"
    - "on the effective capacity of mtc networks in the finite blocklength regime"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"

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)