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 "power control and interference management in dense wireless networks"):
  Abstract: We address the problem of interference management and power control in terms of maximization of a general utility function. For the utility functions under consideration, we propose a power control algorithm based on a fixed-point iteration; further, we prove local convergence of the algorithm in the neighborhood of the optimal power vector. Our algorithm has several benefits over the previously studied works in the literature: first, the algorithm can be applied to problems other than network utility maximization (NUM), e.g., power control in a relay network; second, for a network with $N$ wireless transmitters, the computational complexity of the proposed algorithm is $\mathcal{O}(N^2)$ calculations per iteration (significantly smaller than the $\mathcal{O}(N^3) $ calculations for Newton's iterations or gradient descent approaches). Furthermore, the algorithm converges very fast (usually in less than 15 iterations), and in particular, if initialized close to the optimal solution, the convergence speed is much faster. This suggests the potential of tracking variations in slowly fading channels. Finally, when implemented in a distributed fashion, the algorithm attains the optimal power vector with a signaling/computational complexity of only $\mathcal{O}(N)$ at each node.

Includes members:
  Member "contractive interference functions and rates of convergence of distributed power control laws":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a note on decoding order in optimizing multi cell noma")
  Member "mapel achieving global optimality for a non convex wireless power control problem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sum throughput maximization in multi tag backscattering to multiantenna reader")

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)