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 "throughput maximization for uav aided backscatter communication networks"):
  Abstract: This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks.

Includes members:
  Member "3d trajectory optimization in rician fading for uav enabled data harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "3d uav trajectory and communication design for simultaneous uplink and downlink transmission")
  Member "uav aided offloading for cellular hotspot":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "3d uav trajectory and communication design for simultaneous uplink and downlink transmission")
  Member "securing uav communications via joint trajectory and power control":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "spectral and energy efficient wireless powered iot networks noma or tdma":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "noma enhanced terrestrial and aerial iot networks with partial csi")
  Member "riding on the primary a new spectrum sharing paradigm for wireless powered iot devices":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint time scheduling and transaction fee selection in blockchain based rf powered backscatter cognitive radio network")
  Member "joint trajectory and communication design for multi uav enabled wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "power control in uav supported ultra dense networks communications caching and energy transfer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep reinforcement learning for unmanned aerial vehicle assisted vehicular networks")
  Member "energy efficient data collection in uav enabled wireless sensor network":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")

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)