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: "rate statistics in cellular downlink phy rateless vs adaptive modulation and coding"
  Abstract: In this letter, we focus on rateless coded adaptive transmission in a cellular downlink. Based on a stochastic geometry model for the locations of BSs, we evaluate the meta-distribution of rate, i.e., the distribution of rate conditioned on the point process. An accurate approximation to the distribution of per-user rate is proposed and clearly shown to provide a good match to the simulation results. We quantify the gain in the per-user rate due to physical layer rateless codes relative to the fixed-rate adaptive modulation and coding.

Connected through hyperedge HE-1 (induced by source paper "adaptive transmission in cellular networks do physical layer rateless codes supersede power control"):
  with members:
    - "system level modeling and optimization of the energy efficiency in cellular networks a stochastic geometry framework"
    - "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"
    - "enhanced cellular coverage and throughput using rateless codes"
    - "downlink coordinated joint transmission for mutual information accumulation"
    - "user point processes in cellular networks"
    - "rate splitting for mimo wireless networks a promising phy layer strategy for lte evolution"

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)