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 "optimizing wirelessly powered crowd sensing trading energy for data"):
  Abstract: To overcome the limited coverage in traditional wireless sensor networks, \emph{mobile crowd sensing} (MCS) has emerged as a new sensing paradigm. To achieve longer battery lives of user devices and incentive human involvement, this paper presents a novel approach that seamlessly integrates MCS with wireless power transfer, called \emph{wirelessly powered crowd sensing} (WPCS), for supporting crowd sensing with energy consumption and offering rewards as incentives. The optimization problem is formulated to simultaneously maximize the data utility and minimize the energy consumption for service operator, by jointly controlling wireless-power allocation at the \emph{access point} (AP) as well as sensing-data size, compression ratio, and sensor-transmission duration at \emph{mobile sensor} (MS). Given the fixed compression ratios, the optimal power allocation policy is shown to have a \emph{threshold}-based structure with respect to a defined \emph{crowd-sensing priority} function for each MS. Given fixed sensing-data utilities, the compression policy achieves the optimal compression ratio. Extensive simulations are also presented to verify the efficiency of the contributed mechanisms.

Includes members:
  Member "wireless charging technologies fundamentals standards and network applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "wirelessly powered urban crowd sensing over wearables trading energy for data":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "competitive data trading in wireless powered internet of things iot crowdsensing systems with blockchain")
  Member "ambient rf energy harvesting in ultra dense small cell networks performance and trade offs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "full duplex mimo ofdm communication with self energy recycling")
  Member "resource allocation in wireless powered relay networks a bargaining game approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "energy efficient mobile cloud computing powered by wireless energy transfer":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mobile communications computing and caching resources optimization for coded caching with device computing")
  Member "interactive joint transfer of energy and information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wirelessly powered data aggregation for iot via over the air functional computation beamforming and power control")
  Member "opportunistic wireless energy harvesting in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "mimo broadcasting for simultaneous wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")

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)