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: "coordinated multicell multicast beamforming based on manifold optimization"
  Abstract: Multicast beamforming is a key technology for next-generation wireless cellular networks to support high-rate content distribution services. In this letter, the coordinated downlink multicast beamforming design in multicell networks is considered. The goal is to maximize the minimum signal-to-interference-plus-noise ratio of all users under individual base station power constraints. We exploit the fractional form of the objective function and geometric properties of the constraints to reformulate the problem as a parametric manifold optimization program. Afterwards we propose a low-complexity Dinkelbach-type algorithm combined with adaptive exponential smoothing and Riemannian conjugate gradient iteration, which is guaranteed to converge. Numerical experiments show that the proposed algorithm outperforms the existing SDP-based method and DC-programming-based method and achieves near-optimal performance.

Connected through hyperedge HE-1 (induced by source paper "joint multicast beamforming and user scheduling in large scale antenna systems"):
  with members:
    - "coordinated multicasting with opportunistic user selection in multicell wireless systems"
    - "multicast multigroup beamforming for per antenna power constrained large scale arrays"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "coordinated multicast beamforming in multicell networks"

Connected through hyperedge HE-2 (induced by source paper "mu mimo communications with mimo radar from co existence to joint transmission"):
  with members:
    - "robust mimo beamforming for cellular and radar coexistence"
    - "interference exploitation for radar and cellular coexistence the power efficient approach"
    - "an efficient manifold algorithm for constructive interference based constant envelope precoding"
    - "coexistence analysis between radar and cellular system in los channel"
    - "optimum co design for spectrum sharing between matrix completion based mimo radars and a mimo communication system"
    - "target detection performance of spectrum sharing mimo radars"
    - "manopt a matlab toolbox for optimization on manifolds"

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)