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: "distributed medium access control for energy efficient transmission in cognitive radios"
  Abstract: In the last few years the issue of energy-efficient network design has gained increasingly more importance, both in academia and in industry. Information and communication technologies (ICT) represent about 2% of the entire world's energy consumption, and the situation is likely to reach a point where ICT equipments in large cities will require more energy than is actually available. In this paper we develop and investigate methods for energy efficiency optimization for wireless networks with cognitive units. We show that the problem can be solved without explicit message passing using a modified distributed auction algorithm. Then we introduce a fast converging algorithm that approximates the solution to the maximal energy efficiency problem. We state conditions under which the fast algorithm is asymptotically optimal in terms of the number of users. Finally, we provide simulated examples of the methods developed in this article.

Connected through hyperedge HE-1 (induced by source paper "deep multi user reinforcement learning for distributed dynamic spectrum access"):
  with members:
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "approximate best response dynamics in random interference games"
    - "deep learning in mobile and wireless networking a survey"
    - "deep reinforcement one shot learning for artificially intelligent classification systems"
    - "deep reinforcement learning an overview"
    - "active anomaly detection in heterogeneous processes"
    - "proactive resource management in lte u systems a deep learning perspective"
    - "learning to communicate with deep multi agent reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "distributed channel assignment in cognitive radio networks stable matching and walrasian equilibrium"):
  with members:
    - "a context aware matching game for user association in wireless small cell networks"
    - "fully distributed optimal channel assignment for open spectrum access"
    - "joint sensing and power allocation in nonconvex cognitive radio games nash equilibria and distributed algorithms"
    - "exchange economy in two user multiple input single output interference channels"

Connected through hyperedge HE-3 (induced by source paper "matching theory for future wireless networks fundamentals and applications"):
  with members:
    - "many to many matching games for proactive social caching in wireless small cell networks"
    - "distributed energy efficient channel allocation"
    - "matching with externalities for context aware user cell association in small cell 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.NI(Networking and Internet Architecture)