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 "renewable powered cellular networks energy field modeling and network coverage"):
  Abstract: Powering radio access networks using renewables, such as wind and solar power, promises dramatic reduction in the network operation cost and the network carbon footprints. However, the spatial variation of the energy field can lead to fluctuations in power supplied to the network and thereby affects its coverage. This warrants research on quantifying the aforementioned negative effect and designing countermeasure techniques, motivating the current work. First, a novel energy field model is presented, in which fixed maximum energy intensity    $\gamma$   occurs at Poisson distributed locations, called  energy centers . The intensities fall off from the centers following an exponential decay function of squared distance and the energy intensity at an arbitrary location is given by the decayed intensity from the nearest energy center. The product between the energy center density and the exponential rate of the decay function, denoted as    $\psi$  , is shown to determine the energy field distribution. Next, the paper considers a cellular downlink network powered by harvesting energy from the energy field and analyzes its network coverage. For the case of harvesters deployed at the same sites as base stations (BSs), as    $\gamma$   increases, the mobile outage probability is shown to scale as    $(c\gamma^{-\pi\psi}+p)$  , where    $p$   is the outage probability corresponding to a flat energy field and    $c$   is a constant. Subsequently, a simple scheme is proposed for counteracting the energy randomness by spatial averaging. Specifically, distributed harvesters are deployed in clusters and the generated energy from the same cluster is aggregated and then redistributed to BSs. As the cluster size increases, the power supplied to each BS is shown to converge to a constant proportional to the number of harvesters per BS. Several additional issues are investigated in this paper, including regulation of the power transmission loss in energy aggregation and extensions of the energy field model.

Includes members:
  Member "joint energy and spectrum cooperation for cellular communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a new relation between energy efficiency and spectral efficiency in wireless communications systems")
  Member "spatial throughput of mobile ad hoc networks powered by energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  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 "throughput maximization for the gaussian relay channel with energy harvesting constraints":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "timely updates in energy harvesting two hop networks offline and online policies")
  Member "energy cooperation in cellular networks with renewable powered base stations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "energy sustainable paradigms and methods for future mobile networks a survey")
  Member "fundamentals of heterogeneous cellular networks with energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "medium access control protocols for wireless sensor networks with energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "proportional fairness in aloha networks with rf energy harvesting")
  Member "enabling wireless power transfer in cellular networks architecture modeling and deployment":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cognitive wireless power transfer in the presence of reactive primary communication user")

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)