human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "distributive power control algorithm for multicarrier interference network over time varying fading channels tracking performance analysis and optimization"):
  Abstract: Distributed power control over interference limited network has received an increasing intensity of interest over the past few years. Distributed solutions (like the iterative water-filling, gradient projection, etc.) have been intensively investigated under quasi-static channels. However, as such distributed solutions involve iterative updating and explicit message passing, it is unrealistic to assume that the wireless channel remains unchanged during the iterations. Unfortunately, the behavior of those distributed solutions under time-varying channels is in general unknown. In this paper, we shall investigate the distributed scaled gradient projection algorithm (DSGPA) in a K pairs multicarrier interference network under a finite-state Markov channel (FSMC) model. We shall analyze the convergence property as well as tracking performance of the proposed DSGPA. Our analysis shows that the proposed DSGPA converges to a limit region rather than a single point under the FSMC model. We also show that the order of growth of the tracking errors is given by O(1/N), where N is the average sojourn time of the FSMC. Based on the analysis, we shall derive the tracking error optimal scaling matrices via Markov decision process modeling. We shall show that the tracking error optimal scaling matrices can be implemented distributively at each transmitter. The numerical results show the superior performance of the proposed DSGPA over three baseline schemes, such as the gradient projection algorithm with a constant stepsize.

Includes members:
  Member "multi mode transmission for the mimo broadcast channel with imperfect channel state information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "provisioning energy efficiency and qos for multi carrier comp with limited feedback")
  Member "optimal linear precoding strategies for wideband noncooperative systems based on game theory part i nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "large player games on wireless networks")
  Member "competitive design of multiuser mimo systems based on game theory a unified view":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "optimal linear precoding strategies for wideband non cooperative systems based on game theory part ii algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mixed monotonic programming for fast global optimization")
  Member "limited feedback beamforming over temporally correlated channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "high dimensional stochastic gradient quantization for communication efficient edge learning")
  Member "node based optimal power control routing and congestion control in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal energy and data routing in networks with energy cooperation")

Question: Please tell me which class the source paper 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)