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 "resource allocation in wireless networks with rf energy harvesting and transfer"):
  Abstract: RF energy harvesting and transfer techniques have recently become alternative methods to power the next generation of wireless networks. As this emerging technology enables proactive replenishment of wireless devices, it is advantageous in supporting applications with QoS requirements. This article focuses on the resource allocation issues in wireless networks with RF energy harvesting capability, referred to as RF-energy harvesting networks (RF-EHNs). First we present an overview of the RF-EHNs, followed by a review of a variety of issues regarding resource allocation. Then we present a case study of designing in the receiver operation policy, which is of paramount importance in RF-EHNs. We focus on QoS support and service differentiation, which have not been addressed in previous literature. We also outline open research directions.

Includes members:
  Member "performance analysis of ambient rf energy harvesting with repulsive point process modeling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "robust beamforming for secure communication in systems with wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "wireless networks with rf energy harvesting a contemporary survey":
    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 "dynamic spectrum access in cognitive radio networks with rf energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "compressive spectrum sensing for cognitive radio networks")
  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 "energy efficient optimization for wireless information and power transfer in large scale mimo systems employing energy beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transmission delay minimization in wireless powered communication systems")
  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 "relaying protocols for wireless energy harvesting and information processing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on maximizing information reliability in wireless powered cooperative 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.NI(Networking and Internet Architecture)