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: "power control factor selection in uplink ofdma cellular networks"
  Abstract: Uplink power control plays a key role on the performance of uplink cellular network. In this work, the power control factor ($\in[0,1]$) is evaluated based on three parameters namely: average transmit power, coverage probability and average rate. In other words, we evaluate power control factor such that average transmit power should be low, coverage probability of cell-edge users should be high and also average rate over all the uplink users should be high. We show through numerical studies that the power control factor should be close to $0.5$ in order to achieve an acceptable trade-off between these three parameters.

Connected through hyperedge HE-1 (induced by source paper "spectrum allocation for icic based picocell"):
  with members:
    - "analysis and comparison of coverage probability in the presence of correlated nakagami m interferers and non identical independent nakagami m interferers"
    - "optimal thresholds for coverage and rate in ffr schemes for planned cellular networks"
    - "modeling heterogeneous network interference using poisson point processes"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "analytical evaluation of fractional frequency reuse for heterogeneous cellular networks"
    - "a tractable approach to coverage and rate in cellular networks"
    - "analytical evaluation of fractional frequency reuse for ofdma cellular networks"

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)