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 "sensitive and nonlinear far field rf energy harvesting in wireless communications"):
  Abstract: This paper studies  both  limited sensitivity  and  nonlinearity of far field RF energy harvesting observed in reality and quantifies their effect, attempting to fill a major hole in the simultaneous wireless information and power transfer (SWIPT) literature. RF harvested power is modeled as an arbitrary nonlinear, continuous, and non-decreasing function of received power, by considering limited sensitivity and saturation effects. RF harvester’s sensitivity may be several dBs worse than communications receiver’s sensitivity, potentially rendering RF information signals useless for energy harvesting purposes. Given finite number of datapoint pairs of harvested (output) power and corresponding input power, a piecewise linear approximation is applied and the statistics of the harvested power are offered, as a function of the wireless channel fading statistics. Limited number of datapoints is needed and accuracy analysis is also provided. Case studies include duty-cycled (non-continuous), as well as continuous SWIPT, comparing with industry-level, RF harvesting. The proposed approximation, even though simple, offers  accurate performance  for all studied metrics. On the other hand, linear models or nonlinear-unlimited sensitivity harvesting models deviate from reality, especially in the low-input-power regime. The proposed methodology can be utilized in the current and future SWIPT research.

Includes members:
  Member "waveform design for wireless power transfer with limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "lora backscatter enabling the vision of ubiquitous connectivity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards flexible wireless charging for medical implants using distributed antenna system")
  Member "large scale multiantenna multisine wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cognitive wireless power transfer in the presence of reactive primary communication user")
  Member "secure swipt networks based on a non linear energy harvesting model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic power splitting for swipt with nonlinear energy harvesting in ergodic fading channel")
  Member "max min fair beamforming for swipt systems with non linear eh model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "power efficient and secure wpcns with hardware impairments and non linear eh circuit")
  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 "prototyping and experimentation of a closed loop wireless power transmission with channel acquisition and waveform optimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "asymmetric modulation design for wireless information and power transfer with nonlinear energy harvesting")
  Member "low complexity adaptive multisine waveform design for wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning to communicate and energize modulation coding and multiple access designs for wireless information power transmission")

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)