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 "distributed energy efficient channel allocation"):
  Abstract: Design of energy efficient protocols for modern wireless systems has become an important area of research. In this paper, we propose a distributed optimization algorithm for the channel assignment problem for multiple interfering transceiver pairs that cannot communicate with each other. We first modify the auction algorithm for maximal energy efficiency and show that the problem can be solved without explicit message passing using the carrier sense multiple access (CSMA) protocols. We then develop a novel scheme by converting the channel assignment problem into perfect matchings on bipartite graphs. The proposed scheme improves the energy efficiency and does not require any explicit message passing or a shared memory between the users. We derive bounds on the convergence rate and show that the proposed algorithm converges faster than the distributed auction algorithm and achieves near-optimal performance under Rayleigh fading channels. We also present an asymptotic performance analysis of the fast matching algorithm for energy efficient resource allocation and prove the optimality for large enough number of users and number of channels. Finally, we provide numerical assessments that confirm the energy efficiency gains compared to the state of the art.

Includes members:
  Member "asymptotically optimal resource block allocation with limited feedback":
    also connected through other hyperedges:
      (none)
  Member "distributed learning for channel allocation over a shared spectrum":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine learning for resource management in cellular and iot networks potentials current solutions and open challenges")
  Member "game theoretic dynamic channel allocation for frequency selective interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed learning for channel allocation over a shared spectrum")
  Member "a survey of energy efficient techniques for 5g networks and challenges ahead":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "distributed channel assignment in cognitive radio networks stable matching and walrasian equilibrium":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed learning for channel allocation over a shared spectrum")
  Member "matching theory for future wireless networks fundamentals and applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi agent meta reinforcement learning for self powered and sustainable edge computing systems")
  Member "fully distributed optimal channel assignment for open spectrum access":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed learning for channel allocation over a shared spectrum")
  Member "on optimizing energy efficiency in multi radio multi channel wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint optimization of scheduling and power control in wireless networks multi dimensional modeling and decomposition")

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.NI(Networking and Internet Architecture)