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 "energy efficient cooperative caching in uav networks"):
  Abstract: For an unmanned aerial vehicle (UAV) enabled network we investigate the energy-efficiency (EE) of joint caching and cooperative communication (Fog-RAN). Since UAVs are battery- and cache-limited, placing the popular contents in the caches and managing the energy expenditure of UAVs become crucial. We formulate the energy consumption of UAVs as an aggregate of communication/caching, hovering, and vertical displacement energies, and then devise an optimization problem for optimally assigning contents to caches and choosing the height of UAVs. Adopting tools from stochastic geometry, we also derive the EE in a numerically tractable form as a function of density, the radius of the cooperation zone, cache size, main communication/physical characteristics of UAVs, and influential environmental parameters. We develop two content placement strategies with low computational complexity. The conducted numerical results demonstrate that by adopting these algorithms one is able to improve EE by up to 800% compared to common content placement schemes, e.g., the least-frequently used (LRU), the most-popular, and Hit-rate. Furthermore, while under LRU and Hit-rate schemes there is no benefit in vertically displacing UAVs, under our algorithms one is able to increase EE by at most 600%. Importantly, via our algorithms one can increase the size of cooperation zone in order to steadily increase EE, which is not the cases of LRU, the most-popular, and Hit-rate schemes. We finally observe that there is optimal values for density and cache-size of UAVs, granting maximum EE.

Includes members:
  Member "energy minimization for wireless communication with rotary wing uav":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "random caching based cooperative transmission in heterogeneous wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "joint trajectory and communication design for multi uav enabled wireless networks":
    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 "power control in uav supported ultra dense networks communications caching and energy transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "throughput maximization for uav aided backscatter communication networks")
  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 "overcoming endurance issue uav enabled communications with proactive caching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "uav trajectory optimization for time constrained applications")
  Member "mitigating interference in content delivery networks by spatial signal alignment the approach of shot noise ratio":
    also connected through other hyperedges:
      (none)
  Member "effect of retransmissions on optimal caching in cache enabled small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "stochastic design and analysis of wireless cloud caching 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.IT(Information Theory)