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: "optimal linear precoding strategies for wideband noncooperative systems based on game theory part i nash equilibria"
  Abstract: In this two-part paper, we propose a decentralized strategy, based on a game-theoretic formulation, to find out the optimal precoding/multiplexing matrices for a multipoint-to-multipoint communication system composed of a set of wideband links sharing the same physical resources, i.e., time and bandwidth. We assume, as optimality criterion, the achievement of a Nash equilibrium and consider two alternative optimization problems: 1) the competitive maximization of mutual information on each link, given constraints on the transmit power and on the spectral mask imposed by the radio spectrum regulatory bodies; and 2) the competitive maximization of the transmission rate, using finite order constellations, under the same constraints as above, plus a constraint on the average error probability. In this first part of the paper, we start by showing that the solution set of both noncooperative games is always nonempty and contains only pure strategies. Then, we prove that the optimal precoding/multiplexing scheme for both games leads to a channel diagonalizing structure, so that both matrix-valued problems can be recast in a simpler unified vector power control game, with no performance penalty. Thus, we study this simpler game and derive sufficient conditions ensuring the uniqueness of the Nash equilibrium. Interestingly, although derived under stronger constraints, incorporating for example spectral mask constraints, our uniqueness conditions have broader validity than previously known conditions. Finally, we assess the goodness of the proposed decentralized strategy by comparing its performance with the performance of a Pareto-optimal centralized scheme. To reach the Nash equilibria of the game, in Part II, we propose alternative distributed algorithms, along with their convergence conditions.

Connected through hyperedge HE-1 (induced by source paper "large player games on wireless networks"):
  with members:
    - "discrete power control stochastic game on the multiple access channel"
    - "mean field energy games in wireless networks"
    - "optimal linear precoding strategies for wideband non cooperative systems based on game theory part ii algorithms"

Connected through hyperedge HE-2 (induced by source paper "learning to optimize training deep neural networks for interference management"):
  with members:
    - "detection algorithms for communication systems using deep learning"
    - "deep learning based mimo communications"
    - "learning to learn by gradient descent by gradient descent"
    - "learning to optimize"
    - "why deep neural networks for function approximation"
    - "recurrent neural radio anomaly detection"
    - "signal processing and optimal resource allocation for the interference channel"
    - "base station activation and linear transceiver design for optimal resource management in heterogeneous networks"

Connected through hyperedge HE-3 (induced by source paper "energy efficient power control a look at 5g wireless technologies"):
  with members:
    - "power control in networks with heterogeneous users a quasi variational inequality approach"
    - "energy aware competitive power allocation for heterogeneous networks under qos constraints"
    - "massive mimo with non ideal arbitrary arrays hardware scaling laws and circuit aware design"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "energy efficient scheduling and power allocation in downlink ofdma networks with base station coordination"
    - "massive mimo for maximal spectral efficiency how many users and pilots should be allocated"
    - "five disruptive technology directions for 5g"
    - "energy efficiency optimization for mimo broadcast channels"

Connected through hyperedge HE-4 (induced by source paper "new algorithms for maximizing cellular wireless network energy efficiency"):
  with members:
    - "energy efficient resource allocation for fractional frequency reuse in heterogeneous networks"
    - "energy efficient scheduling and power allocation in downlink ofdma networks with base station coordination"
    - "decomposition by partial linearization parallel optimization of multi agent systems"
    - "quantifying potential energy efficiency gain in green cellular wireless networks"
    - "framework for link level energy efficiency optimization with informed transmitter"

Connected through hyperedge HE-5 (induced by source paper "game theory for signal processing in networks"):
  with members:
    - "understanding game theory via wireless power control"
    - "crawford sobel meet lloyd max on the grid"
    - "coalitional games in miso interference channels epsilon core and coalition structure stable set"
    - "multiobjective signal processing optimization the way to balance conflicting metrics in 5g systems"
    - "distributed cooperative sensing in cognitive radio networks an overlapping coalition formation approach"
    - "distributed adaptive networks a graphical evolutionary game theoretic view"
    - "jamming games in the mimo wiretap channel with an active eavesdropper"
    - "distributed learning policies for power allocation in multiple access channels"

Connected through hyperedge HE-6 (induced by source paper "energy aware competitive power allocation for heterogeneous networks under qos constraints"):
  with members:
    - "power control in networks with heterogeneous users a quasi variational inequality approach"
    - "what will 5g be"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "designing multi user mimo for energy efficiency when is massive mimo the answer"
    - "framework for link level energy efficiency optimization with informed transmitter"
    - "energy efficient precoding for multiple antenna terminals"
    - "competitive design of multiuser mimo systems based on game theory a unified view"
    - "distributed power allocation with rate constraints in gaussian parallel interference channels"

Connected through hyperedge HE-7 (induced by source paper "power control in networks with heterogeneous users a quasi variational inequality approach"):
  with members:
    - "game theory for signal processing in networks"
    - "energy aware competitive power allocation for heterogeneous networks under qos constraints"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "framework for link level energy efficiency optimization with informed transmitter"
    - "energy efficient precoding for multiple antenna terminals"
    - "competitive design of multiuser mimo systems based on game theory a unified view"
    - "optimal linear precoding strategies for wideband non cooperative systems based on game theory part ii algorithms"

Connected through hyperedge HE-8 (induced by source paper "pricing based distributed energy efficient beamforming for miso interference channels"):
  with members:
    - "energy efficient power control a look at 5g wireless technologies"
    - "what will 5g be"
    - "framework for link level energy efficiency optimization with informed transmitter"
    - "introducing hierarchy in energy games"
    - "a distributed merge and split algorithm for fair cooperation 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.IT(Information Theory)