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: "spectrum coordination in energy efficient cognitive radio networks"
  Abstract: Device coordination in open spectrum systems is a challenging problem, particularly since users experience varying spectrum availability over time and in different locations. In this paper, we propose a game-theoretic approach that allows cognitive radio (CR) pairs, namely the primary user (PU) and the secondary user (SU), to update their transmission power and frequencies simultaneously. Specifically, we address a Stackelberg game model in which individual users attempt to hierarchically access to the wireless spectrum while maximizing their energy efficiency. A thorough analysis of the existence, uniqueness, and characterization of the Stackelberg equilibrium (SE) is conducted. In particular, we show that a spectrum coordination naturally occurs when both actors in the system decide sequentially about their power and their transmitting carriers. As a result, spectrum sensing in such a situation turns out to be a simple detection of the presence/absence of a transmission on each subband. We also show that when users experience very different channel gains on their two carriers, they may choose to transmit on the same carrier at the SE as this contributes enough energy efficiency to outweigh the interference degradation caused by the mutual transmission. Then, we provide an algorithmic analysis on how the PU and the SU can reach such a spectrum coordination using an appropriate learning process. We validate our results through extensive simulations and compare the proposed algorithm to some typical scenarios, including the non-cooperative case in the work of Meshkati  et al.  and the throughput-based-utility systems. Typically, it is shown that the proposed Stackelberg decision approach optimizes the energy efficiency while still maximizing the throughput at the equilibrium.

Connected through hyperedge HE-1 (induced by source paper "game theory for multi access edge computing survey use cases and future trends"):
  with members:
    - "non cooperative game theory based rate adaptation for dynamic video streaming over http"
    - "fog computing a taxonomy survey and future directions"
    - "optimal pricing for a peer to peer sharing platform under network externalities"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "a survey on mobile edge computing the communication perspective"
    - "sustainable incentives for mobile crowdsensing"
    - "multi agent reinforcement learning in sequential social dilemmas"
    - "mobile edge computing a survey on architecture and computation offloading"

Connected through hyperedge HE-2 (induced by source paper "survey of game theory and future trends with application to emerging wireless data communication networks"):
  with members:
    - "non cooperative game theory based rate adaptation for dynamic video streaming over http"
    - "fog computing a taxonomy survey and future directions"
    - "a survey on mobile edge computing the communication perspective"
    - "sustainable incentives for mobile crowdsensing"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "game theory models for communication between agents a review"
    - "game theoretic multi agent control and network cost allocation under communication constraints"
    - "a survey on applications of model free strategy learning in cognitive wireless networks"

Connected through hyperedge HE-3 (induced by source paper "on the two user multi carrier joint channel selection and power control game"):
  with members:
    - "toward fully coordinated multi level multi carrier energy efficient networks"
    - "on the energy spectral efficiency trade off of the mrc receiver in massive mimo systems with transceiver power consumption"
    - "spectral efficiency and energy efficiency of ofdm systems impact of power amplifiers and countermeasures"
    - "quantifying potential energy efficiency gain in green cellular wireless networks"
    - "a game theoretic analysis for energy efficient heterogeneous networks"
    - "energy efficient precoding for multiple antenna terminals"
    - "introducing hierarchy in energy games"
    - "femtocell networks a survey"

Connected through hyperedge HE-4 (induced by source paper "toward fully coordinated multi level multi carrier energy efficient networks"):
  with members:
    - "on the energy spectral efficiency trade off of the mrc receiver in massive mimo systems with transceiver power consumption"
    - "spectral efficiency and energy efficiency of ofdm systems impact of power amplifiers and countermeasures"
    - "spectral and energy efficiency trade off with joint power bandwidth allocation in ofdma networks"
    - "a game theoretic analysis for energy efficient heterogeneous networks"
    - "femtocell networks a survey"
    - "energy efficient resource allocation in wireless 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.GT(Computer Science and Game Theory)