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 "large scale multiantenna multisine wireless power transfer"):
  Abstract: Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things. Multi-antenna multi-sine waveforms adaptive to the channel state information have been shown to be a promising building block of WPT. However, the current design is computationally too complex to be applied to large-scale WPT, where signals are sent across a large number (tens) of antennas and frequencies. This paper proposes efficient single/multi-user algorithms based on a generalizable optimization framework, in order to design transmit waveforms that maximize the weighted-sum/minimum rectenna output DC voltage. The study highlights the significant effect of the nonlinearity of the rectenna on the design of waveforms in single/multi-user systems. Interestingly, in the single-user case, the optimal spatial beamforming, obtained before optimizing power allocation across frequencies, turns out to be maximum ratio transmission. Nevertheless, in the general multi-user weighted-sum criterion maximization problem, optimizations in the frequency and the spatial domains are coupled. Assuming channel hardening, we also propose low-complexity algorithms based on asymptotic analysis, where the structure of the asymptotically optimal spatial beamforming can be found before optimizations. Simulation results confirm the inefficiency of the linear model-based design in single/multi-user systems. Moreover, simulation results show that the proposed algorithms (based on the nonlinear model) can benefit from an increasing number of sinewaves at a computational cost much lower than the existing method. Simulation results also indicate that the large-scale WPT architecture can boost the end-to-end power transfer efficiency and the transmission range.

Includes members:
  Member "low complexity adaptive multisine waveform design for wireless power transfer":
    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 "waveform design for wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "waveform optimization for large scale multi antenna multi sine wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "waveform design for wireless power transfer with limited feedback")
  Member "relaying strategies for wireless powered mimo relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "energy efficiency fairness for multi pair wireless powered relaying systems")
  Member "communications and signals design for wireless power transmission":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "massive mimo multicasting in noncooperative cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint unicast and multi group multicast transmission in massive mimo systems")
  Member "energy beamforming with one bit feedback":
    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 "optimized training design for wireless energy 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)