human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the convex properties of wireless power transfer with nonlinear energy harvesting"):
  Abstract: The convex property of a nonlinear wireless power transfer (WPT) is characterized in this work. Following a nonlinear energy harvesting model, we express the relationship between the harvested direct current (DC) power and the power of the received radio-frequency signal via an implicit function, based on which the convex property is further proved. In particular, for a predefined rectifier's input signal distribution, we show that the harvested DC power of the nonlinear model is convex in the reciprocal of the rectifier's input signal power. Finally, we provide an example to show the advantages of applying the convex property in WPT network designs.

Includes members:
  Member "signal and system design for wireless power transfer prototype experiment and validation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to communicate and energize modulation coding and multiple access designs for wireless information power transmission")
  Member "fundamentals of wireless information and power transfer from rf energy harvester models to signal and system designs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "heterogeneous power splitting based two way df relaying with non linear energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "system outage performance for three step two way energy harvesting df relaying")
  Member "on the beneficial roles of fading and transmit diversity in wireless power transfer with nonlinear energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "on capacity achieving distributions over complex awgn channels under nonlinear power constraints and their applications to swipt":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning to communicate and energize modulation coding and multiple access designs for wireless information power transmission")
  Member "wireless information and power transfer over an awgn channel nonlinearity and asymmetric gaussian signaling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to communicate and energize modulation coding and multiple access designs for wireless information power transmission")
  Member "robust resource allocation for mimo wireless powered communication networks based on a non linear eh model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "waveform design for wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")

Question: Please tell me which class the source paper 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)