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 "joint sensing and power allocation in nonconvex cognitive radio games nash equilibria and distributed algorithms"):
  Abstract: In this paper, we propose a novel class of Nash problems for Cognitive Radio (CR) networks, modeled as Gaussian frequency-selective interference channels, wherein each secondary user (SU) competes against the others to maximize his own opportunistic throughput by choosing jointly the sensing duration, the detection thresholds, and the vector power allocation. The proposed general formulation allows to accommodate several (transmit) power and (deterministic/probabilistic) interference constraints, such as constraints on the maximum individual and/or aggregate (probabilistic) interference tolerable at the primary receivers. To keep the optimization as decentralized as possible, global (coupling) interference constraints are imposed by penalizing each SU with a set of time-varying prices based upon his contribution to the total interference; the prices are thus additional variable to optimize. The resulting players' optimization problems are nonconvex; moreover, there are possibly price clearing conditions associated with the global constraints to be satisfied by the solution. All this makes the analysis of the proposed games a challenging task; none of classical results in the game theory literature can be successfully applied. The main contribution of this paper is to develop a novel optimization-based theory for studying the proposed nonconvex games; we provide a comprehensive analysis of the existence and uniqueness of a standard Nash equilibrium, devise alternative best-response based algorithms, and establish their convergence.

Includes members:
  Member "real and complex monotone communication games":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on cyber risk management of blockchain networks a game theoretic approach")
  Member "joint sensing and power allocation in nonconvex cognitive radio games quasi nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a new distributed dc programming method and its applications")
  Member "game theory and the frequency selective interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "channel equilibrium networks for learning deep representation")
  Member "optimal multiband joint detection for spectrum sensing in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimization of the belief propagation algorithm for distributed detection by linear data fusion techniques")
  Member "optimal linear precoding strategies for wideband noncooperative systems based on game theory part i nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "large player games on wireless networks")
  Member "distributed decision through self synchronizing sensor networks in the presence of propagation delays and nonreciprocal channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed inference for relay assisted sensor networks with intermittent measurements over fading channels")

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)