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: "a new energy efficient beamforming strategy for miso interfering broadcast channels based on large systems analysis"
  Abstract: In this paper, we propose a new beamforming design to maximize energy efficiency (EE) for multiple input single output interfering broadcast channels (IFBC). Under this model, the EE problem is non-convex in general due to the coupled interference and its fractional form, and thus it is difficult to solve the problem. Conventional algorithms which address this problem have adopted an iterative method for each channel realization, which requires high computational complexity. In order to reduce the computational complexity, we parameterize the beamforming vector by scalar parameters related to beam direction and power. Then, by employing asymptotic results of random matrix theory with this parametrization, we identify the optimal parameters to maximize the EE in the large system limit assuming that the number of transmit antennas and users are large with a fixed ratio. In the asymptotic regime, our solutions depend only on the second order channel statistics, which yields significantly reduced computational complexity and system overhead compared to the conventional approaches. Hence, the beamforming vector to maximize the EE performance can be determined with local channel state information and the optimized parameters. Based on the asymptotic results, the proposed scheme can provide insights on the average EE performance, and a simple yet efficient beamforming strategy is introduced for the finite system case. Numerical results confirm that the proposed scheme shows a negligible performance loss compared to the best result achieved by the conventional approaches even with small system dimensions, with much reduced system complexity.

Connected through hyperedge HE-1 (induced by source paper "joint design of fronthauling and hybrid beamforming for downlink c ran systems"):
  with members:
    - "channel diagonalization for cloud radio access"
    - "stochastic successive convex optimization for two timescale hybrid precoding in massive mimo"
    - "energy efficiency maximization for c rans discrete monotonic optimization penalty and ell _ 0 approximation methods"
    - "hybrid analog digital beamforming for massive mimo systems"
    - "multi user precoding and channel estimation for hybrid millimeter wave systems"
    - "hybrid precoding for massive mimo systems in cloud ran architecture with capacity limited fronthauls"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "subspace estimation and decomposition for large millimeter wave mimo systems"

Connected through hyperedge HE-2 (induced by source paper "uav aided wireless communication designs with propulsion energy limitations"):
  with members:
    - "uav aided offloading for cellular hotspot"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "spectrum sharing and cyclical multiple access in uav aided cellular offloading"
    - "cyclical multiple access in uav aided communications a throughput delay tradeoff"
    - "energy efficient uav communication with trajectory optimization"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "energy efficiency optimization for mimo broadcast channels"

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)