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 "performance analysis of ambient rf energy harvesting a stochastic geometry approach"):
  Abstract: Ambient RF (Radio Frequency) energy harvesting techniques have recently been proposed as a potential solution to provide proactive energy replenishment for wireless devices. This paper aims to analyze the performance of a battery-free wireless sensor powered by ambient RF energy harvesting using a stochastic-geometry approach. Specifically, we consider a random network model in which ambient RF sources are distributed as a Ginibre α-determinantal point process which recovers the Poisson point process when α approaches zero. We characterize the expected RF energy harvesting rate. We also perform a worst-case study which derives the upper bounds of both power outage and transmission outage probabilities. Numerical results show that our upper bounds are accurate and that better performance is achieved when the distribution of ambient sources exhibits stronger repulsion.

Includes members:
  Member "resource allocation in wireless networks with rf energy harvesting and transfer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "experiment modeling and analysis of wireless powered sensor network for energy neutral power management")
  Member "wireless networks with rf energy harvesting a contemporary survey":
    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 "dynamic spectrum access in cognitive radio networks with rf energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "compressive spectrum sensing for cognitive radio networks")
  Member "cognitive and energy harvesting based d2d communication in cellular networks stochastic geometry modeling and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  Member "simultaneous information and energy transfer in large scale networks with without relaying":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "relay selection scheduling and power control in wireless powered cooperative communication networks")
  Member "a layered coalitional game framework of wireless relay network":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "collaborative smartphone sensing using overlapping coalition formation games")
  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 "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)