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: "design of ambient backscatter training for retrodirective wireless power transfer"
  Abstract: Wireless power transfer (WPT) using energy beamforming is a promising solution for low power devices in the future Internet of Things (IoT). In this work, we propose a WPT scenario with a retrodirective antenna at the energy transmitter (ET) and ambient backscatter at the energy receiver (ER). The retrodirective WPT at the ET eliminates the requirement of knowing the channel from the ET to ER, and the use of ambient backscattering (as opposed to active transmission) minimizes the energy consumption at the ER. We propose a training sequence design, i.e., the pattern of varying the reflection coefficient at the ER, to eliminate the direct-link interference from the ambient source. We show that when the ambient symbol duration is known, the ambient interference is fully cancelled by using the proposed design. We analytically model the system and derive a closed-form expression for the average harvested power at the ER, assuming that the retrodirective array size is large. Our results show that with practical parameter values, the proposed solution is robust to a small timing offset mismatch at the correlator and allows the ER to successfully harvest tens of $\mu$W of power, which is an important improvement for low-power IoT devices.

Connected through hyperedge HE-1 (induced by source paper "a retrodirective wireless power transfer scheme for ambient backscatter systems"):
  with members:
    - "retrodirective large antenna energy beamforming in backscatter multi user networks"
    - "retrodirective multi user wireless power transfer with massive mimo"
    - "modulation in the air backscatter communication over ambient ofdm carrier"
    - "performance analysis of massive mimo for cell boundary users"
    - "joint wireless information and energy transfer with reduced feedback in mimo interference channels"
    - "energy beamforming with one bit feedback"
    - "joint beamforming design for multi user wireless information and power transfer"
    - "optimized training design for wireless energy 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)