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 "spatial throughput maximization of wireless powered communication networks"):
  Abstract: Wireless charging is a promising way to power wireless nodes' transmissions. This paper considers new dual-function access points (APs), which are able to support the energy/information transmission to/from wireless nodes. We focus on a large-scale wireless powered communication network (WPCN), and use stochastic geometry to analyze the wireless nodes' performance tradeoff between energy harvesting and information transmission. We study two cases with battery-free and battery-deployed wireless nodes. For both cases, we consider a harvest-then-transmit protocol by partitioning each time frame into a downlink (DL) phase for energy transfer, and an uplink (UL) phase for information transfer. By jointly optimizing frame partition between the two phases and the wireless nodes' transmit power, we maximize the wireless nodes' spatial throughput subject to a successful information transmission probability constraint. For the battery-free case, we show that the wireless nodes prefer to choose small transmit power to obtain large transmission opportunity. For the battery-deployed case, we first study an ideal infinite-capacity battery scenario for wireless nodes, and show that the optimal charging design is not unique, due to the sufficient energy stored in the battery. We then extend to the practical finite-capacity battery scenario. Although the exact performance is difficult to be obtained analytically, it is shown to be upper and lower bounded by those in the infinite-capacity battery scenario and the battery-free case, respectively. Finally, we provide numerical results to corroborate our study.

Includes members:
  Member "on spatial capacity of wireless ad hoc networks with threshold based scheduling":
    also connected through other hyperedges:
      (none)
  Member "spatial throughput of mobile ad hoc networks powered by energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  Member "throughput maximization in wireless powered communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "opportunistic wireless energy harvesting in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "fundamentals of heterogeneous cellular networks with energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "downlink rate distribution in heterogeneous cellular networks under generalized cell selection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "throughput optimal policies for energy harvesting wireless transmitters with non ideal circuit power":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "radio frequency energy harvesting and management for wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal spectrum sensing policy in rf powered cognitive radio networks")

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)