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 multicell beamforming design approaching pareto boundary with max min fairness"
  Abstract: This paper addresses coordinated downlink beamforming optimization in multicell time division duplex (TDD) systems where a small number of parameters are exchanged between cells but with no data sharing. With the goal to reach the point on the Pareto boundary with max-min rate fairness, we first develop a two-step centralized optimization algorithm to design the joint beamforming vectors. This algorithm can achieve a further sum-rate improvement over the max-min optimal performance, and is shown to guarantee max-min Pareto optimality for scenarios with two base stations (BSs) each serving a single user. To realize a distributed solution with limited intercell communication, we then propose an iterative algorithm by exploiting an approximate uplink-downlink duality, in which only a small number of positive scalars are shared between cells in each iteration. Simulation results show that the proposed distributed solution achieves a fairness rate performance close to the centralized algorithm while it has a better sum-rate performance, and demonstrates a better tradeoff between sum-rate and fairness than the Nash Bargaining solution especially at high signal-to-noise ratio.

Connected through hyperedge HE-1 (induced by source paper "an overview of data importance aware radio resource management for edge machine learning"):
  with members:
    - "energy efficient radio resource allocation for federated edge learning"
    - "edge intelligence paving the last mile of artificial intelligence with edge computing"
    - "efficient decentralized deep learning by dynamic model averaging"
    - "deepcode feedback codes via deep learning"
    - "federated learning strategies for improving communication efficiency"
    - "wireless data acquisition for edge learning data importance aware retransmission"
    - "towards an intelligent edge wireless communication meets machine learning"
    - "end to end learning of communications systems without a channel model"

Connected through hyperedge HE-2 (induced by source paper "distributed optimization for coordinated beamforming in multicell multigroup multicast systems power minimization and sinr balancing"):
  with members:
    - "energy efficient beam coordination strategies with rate dependent processing power"
    - "cooperative channel estimation for coordinated transmission with limited backhaul"
    - "distributed coordinated beamforming for multi cell multigroup multicast systems"
    - "precoding in multibeam satellite communications present and future challenges"
    - "multicast multigroup precoding and user scheduling for frame based satellite communications"
    - "multicast multigroup beamforming under per antenna power constraints"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"
    - "coordinated multicast beamforming in multicell networks"

Connected through hyperedge HE-3 (induced by source paper "distributed coordinated beamforming for multi cell multigroup multicast systems"):
  with members:
    - "sum rate maximizing multigroup multicast beamforming under per antenna power constraints"
    - "multicast multigroup beamforming under per antenna power constraints"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"
    - "coordinated multicast beamforming in multicell networks"

Connected through hyperedge HE-4 (induced by source paper "optimal dynamic point selection for power minimization in multiuser downlink comp"):
  with members:
    - "large system analysis of base station cooperation for power minimization"
    - "joint beamforming and power control in coordinated multicell max min duality effective network and large system transition"
    - "large system analysis of cooperative multi cell downlink transmission via regularized channel inversion with imperfect csit"
    - "base station cooperation on the downlink large system analysis"

Connected through hyperedge HE-5 (induced by source paper "multicell coordinated beamforming with rate outage constraint part ii efficient approximation algorithms"):
  with members:
    - "signal processing and optimal resource allocation for the interference channel"
    - "multicell coordinated beamforming with rate outage constraint part i complexity analysis"
    - "coordinated beamforming for multiuser miso interference channel under rate outage constraints"
    - "achievable outage rate regions for the miso interference channel"
    - "outage probability and outage based robust beamforming for mimo interference channels with imperfect channel state information"
    - "robust monotonic optimization framework for multicell miso systems"
    - "achieving global optimality for weighted sum rate maximization in the k user gaussian interference channel with multiple antennas"
    - "optimality properties distributed strategies and measurement based evaluation of coordinated multicell ofdma transmission"

Connected through hyperedge HE-6 (induced by source paper "backhaul limited asymmetric cooperation for mimo cellular networks via semidefinite relaxation"):
  with members:
    - "a decentralized method for joint admission control and beamforming in coordinated multicell downlink"
    - "a fast approach for overcomplete sparse decomposition based on smoothed ell 0 norm"
    - "networked mimo with clustered linear precoding"

Connected through hyperedge HE-7 (induced by source paper "max min energy efficient beamforming for multicell multiuser joint transmission systems"):
  with members:
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "energy efficiency optimization for mimo broadcast channels"
    - "cooperative multi cell block diagonalization with per base station power constraints"
    - "adaptive limited feedback for sum rate maximizing beamforming in cooperative multicell systems"

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)