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 "backscatter communications for the internet of things a stochastic geometry approach"):
  Abstract: Powering the massive number of small computing devices in the Internet of Things (IoT) is a major challenge because replacing their batteries or powering them with wires is very expensive and impractical. A viable option to enable a perpetual network operation is through the use of far-field Wireless Power Transfer (WPT). We study a large network architecture that uses a combination of WPT and backscatter communication. The network consists of power beacons (PBs) and passive backscatter nodes (BNs), and their locations are modeled as points of independent Poisson point processes (PPPs). The PBs transmit a sinusoidal continuous wave (CW) and the BNs reflect back a portion of this signal while harvesting the remaining part. A BN harvests energy from multiple nearby PBs and modulates its information bits on the composite CW through backscatter modulation. The analysis poses real challenges due to the double fading channel, and its dependence on the PPPs of both BNs and PBs. With the help of stochastic geometry, we derive the coverage probability and the capacity of the network in tractable and easily computable expressions. These expressions depend on the density of both PB and BN, both forward and backward path loss exponents, transmit power of the PB, backscattering efficiency, and number of PBs in a harvesting region. We observe that the coverage probability decreases with an increase in the density of the BNs, while the capacity of the network improves. We compare the performance of this network with a regular powered network in which the BNs have a reliable power source and show that for certain parameters the coverage of the former network approaches that of the regular powered network.

Includes members:
  Member "backscatter communications for internet of things theory and applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "uav data collection over noma backscatter networks uav altitude and trajectory optimization")
  Member "multistatic scatter radio sensor networks for extended coverage":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "backscatter data collection with unmanned ground vehicle mobility management and power allocation")
  Member "joint uplink and downlink coverage analysis of cellular based rf powered iot network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "backscatter communications for wireless powered sensor networks with collision resolution":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coverage probability analysis under clustered ambient backscatter nodes")
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "downlink and uplink decoupling in two tier heterogeneous networks with multi antenna base stations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "treating interference as noise in cellular networks a stochastic geometry approach")
  Member "modulation in the air backscatter communication over ambient ofdm carrier":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a retrodirective wireless power transfer scheme for ambient backscatter systems")
  Member "waveform design for wireless power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")

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)