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 "opportunistic wireless energy beamforming using rssi feedback"):
  Abstract: This paper proposes a novel channel estimation method, and a cluster-based opportunistic scheduling policy, that enhances the efficiency of wireless energy transfer in a system consisting of multiple energy receivers (ERs). Firstly, in the training stage, the energy transmitter (ET) obtains a set of RSSI feedback values from all ERs, and these values are used to estimate the channels between the ET and all ERs. Next, based on the channel estimates, the ERs are grouped into clusters, and the cluster that has its members closest to its centroid in phase is picked. This cluster will be given priority, and the beamformer that maximizes the minimum harvested energy among all ERs in the selected cluster is found by solving a convex optimization problem. This beamformer is used to transfer energy to the ERs using maximum ratio transmit beamforming. All ERs have the same chance of being selected regardless of their distances from the ET, and hence, this scheduling policy can be considered to be opportunistic as well as fair. It is shown that the proposed method achieves significant performance gains.

Includes members:
  Member "wireless energy transfer to a pair of energy receivers using signal strength feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cluster based wireless energy transfer for low complex energy receivers")
  Member "wireless energy beamforming using received signal strength indicator feedback":
    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 "over the air implementation of uplink noma":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cluster based wireless energy transfer for low complex energy receivers")
  Member "on the efficiency of far field wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cognitive wireless power transfer in the presence of reactive primary communication user")
  Member "optimized training for net energy maximization in multi antenna wireless energy transfer over frequency selective channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cognitive wireless power transfer in the presence of reactive primary communication user")
  Member "energy beamforming with one bit feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "throughput maximization in wireless powered communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "spatially selective artificial noise aided transmit optimization for miso multi eves secrecy rate maximization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "secure millimeter wave cloud radio access networks relying on microwave multicast fronthaul")

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)