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 data collection with unmanned ground vehicle mobility management and power allocation"):
  Abstract: Collecting data from the massive Internet of Things (IoT) devices is a challenging task since communication circuits are power-demanding while energy supply at IoT devices is limited. To overcome this challenge, backscatter communication emerges as a promising solution as it eliminates radio frequency components in the IoT devices. Unfortunately, the transmission range of backscatter communication is short. To facilitate backscatter communication, this paper proposes to integrate unmanned ground vehicle (UGV) with backscatter data collection. With such a scheme, the UGV could improve the communication quality by approaching various IoT devices. However, moving also costs energy consumption and a fundamental question is: what is the right balance between spending energy on moving versus on communication? To answer this question, this paper studies energy minimization under a joint graph mobility and backscatter communication model. With the joint model, the mobility management and power allocation problem, unfortunately, involves nonlinear coupling between discrete variables brought by mobility and continuous variables brought by communication. Despite the optimization challenges, an algorithm that theoretically achieves the minimum energy consumption is derived, and it leads to automatic trade-off between spending energy on moving versus on communication in the UGV backscatter system. The simulation results show that if the noise power is small (e.g., ≤−100 dBm), the UGV should collect the data with small movements. However, if the noise power is increased to a larger value (e.g., −60 dBm), the UGV should spend more motion energy to get closer to the IoT users.

Includes members:
  Member "energy constrained uav trajectory design for ground node localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "localization in ultra narrow band iot networks design guidelines and tradeoffs")
  Member "resource allocation for solar powered uav communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mini unmanned aerial vehicle based remote sensing techniques applications and prospects")
  Member "aerial anchors positioning for reliable rss based outdoor localization in urban environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tutorial on uav a blue sky view on wireless communication")
  Member "wirelessly powered backscatter communications waveform design and snr energy tradeoff":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "energy efficiency of distributed antenna systems with wireless power transfer")
  Member "joint trajectory and communication design for multi uav enabled wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "inference from randomized transmissions by many backscatter sensors":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "over the air computation systems optimization analysis and scaling laws")
  Member "multistatic scatter radio sensor networks for extended coverage":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint communication and motion energy minimization in ugv backscatter communication")
  Member "full duplex backscatter interference networks based on time hopping spread spectrum":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a survey of electromagnetic side channel attacks and discussion on their case progressing potential for digital forensics")

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)