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 "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.

Includes members:
  Member "a game theoretic analysis for energy efficient heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed power control with partial channel state information performance characterization and design")
  Member "distributed learning policies for power allocation in multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "low complexity distributed radio access network slicing algorithms and experimental results")
  Member "introducing hierarchy in energy games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed power control with partial channel state information performance characterization and design")
  Member "femtocell networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust resource allocation for pd noma based miso heterogeneous networks with comp technology")
  Member "energy efficient resource allocation in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "spectral efficiency of spectrum pooling systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the two user multi carrier joint channel selection and power control game")

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.GT(Computer Science and Game Theory)