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 "throughput optimization in fdd mu miso wireless powered communication networks"):
  Abstract: In this paper, we consider a frequency-division duplexing (FDD) multiple-user multiple-input-single-output (MU-MISO) wireless-powered communication network (WPCN) consisting of one hybrid data-and-energy access point (HAP) with multiple antennas which coordinates energy/information transfer to/from several single-antenna wireless devices (WD). Typically, in such a system, wireless energy transfer (WET) requires such techniques as energy beamforming (EB) for efficient transfer of energy to the WDs. Yet, efficient EB can only be accomplished if channel state information (CSI) is available to the transmitter, which, in FDD systems is only achieved through uplink (UL) feedback. Therefore, while in our scheme we use the downlink (DL) channels for WET only, the UL channel frames are split into two phases: the CSI feedback phase during which the WDs feed CSI back to the HAP and the WIT phase where the HAP performs wireless information transmission (WIT) via space-division-multiple-access (SDMA). To ensure rate fairness among the WDs, this paper maximizes the minimum WIT data rate among the WDs. Using an iterative solution, the original optimization problem can be relaxed into two sub-problems whose convexity conditions are derived. Finally, the behavior of this system when the number of HAP antennas increases is analyzed. Simulation results verify the truthfulness of our analysis.

Includes members:
  Member "wireless powered communication networks tdd or fdd":
    also connected through other hyperedges:
      (none)
  Member "maximizing ergodic throughput in wireless powered communication networks":
    also connected through other hyperedges:
      (none)
  Member "distributed wireless power transfer with energy 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 "wireless power meets energy harvesting a joint energy allocation approach in ofdm based system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal energy allocation and task offloading policy for wireless powered mobile edge computing systems")
  Member "on the feasibility of wireless energy transfer using massive antenna arrays":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "a general design framework for mimo wireless energy transfer with limited feedback":
    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 "wireless powered communication networks an overview":
    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 "wireless powered communication opportunities and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)