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: "magnetic beamforming for wireless power transfer"
  Abstract: Magnetic resonant coupling (MRC) is an efficient method for realizing the near-field wireless power transfer (WPT). The use of multiple transmitters (TXs) each with one coil can be applied to enhance the WPT performance by coherently combining the magnetic fields induced by all TX coils in a beam toward the receiver (RX) coil, a technique termed "magnetic beamforming". In this paper, we study the optimal magnetic beamforming design for an MRC-WPT system with multiple TXs and a single RX. We formulate a problem to jointly optimize the currents flowing through different TXs so as to minimize the total power drawn from their voltage sources, subject to the minimum power required by the RX load as well as the practical constraints on the peak voltage and current at all TXs. For the special case of identical TX resistances and without the peak voltage and current constraints, we show that the optimal current at each TX should be proportional to the mutual inductance between its TX coil and the RX coil. In general, the problem is a non-convex quadratically constrained quadratic programming (QCQP), which is reformulated as a semidefinite programming (SDP) with rank-one constraint. We show that the semidefinite relaxation (SDR) of the reformulated problem is tight and hence the problem is solved optimally. Numerical results show that the optimal magnetic beamforming design significantly enhances the deliverable power as well as the power efficiency over the uncoordinated WPT benchmark with equal current allocation over TXs.

Connected through hyperedge HE-1 (induced by source paper "node placement and distributed magnetic beamforming optimization for wireless power transfer"):
  with members:
    - "multiuser wireless power transfer via magnetic resonant coupling performance analysis charging control and power region characterization"
    - "wireless powered communication networks an overview"
    - "beamforming for magnetic induction based wireless power transfer systems with multiple receivers"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "mimo broadcasting for simultaneous wireless information and power transfer"

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)