human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
  Abstract: Integrating the unmanned aerial vehicles (UAVs) into the cellular network is envisioned to be a promising technology to significantly enhance the communication performance of both UAVs and existing terrestrial users. In this paper, we first provide an overview on the two main paradigms in cellular UAV communications, i.e., cellular-enabled UAV communication with UAVs as new aerial users served by the ground base stations (GBSs), and UAV-assisted cellular communication with UAVs as new aerial communication platforms serving the terrestrial users. Then, we focus on the former paradigm and study a new UAV trajectory design problem subject to practical communication connectivity constraints with the GBSs. Specifically, we consider a cellular-connected UAV in the mission of flying from an initial location to a final location, during which it needs to maintain reliable communication with the cellular network by associating with one GBS at each time instant. We aim to minimize the UAV's mission completion time by optimizing its trajectory, subject to a quality-of-connectivity constraint of the GBS-UAV link specified by a minimum receive signal-to-noise ratio target. To tackle this challenging non-convex problem, we first propose a graph connectivity based method to verify its feasibility. Next, by examining the GBS-UAV association sequence over time, we obtain useful structural results on the optimal UAV trajectory, based on which two efficient methods are proposed to find high-quality approximate trajectory solutions by leveraging graph theory and convex optimization techniques. The proposed methods are analytically shown to be capable of achieving a flexible trade-off between complexity and performance, and yielding a solution that is arbitrarily close to the optimal solution in polynomial time. Finally, we make concluding remarks and point out some promising directions for future work.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations"):
  with members:
    - "optimizing joint probabilistic caching and channel access for clustered d2d networks"
    - "3gpp inspired stochastic geometry based mobility model for a drone cellular network"
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"

Connected through hyperedge HE-2 (induced by source paper "joint 3d maneuver and power adaptation for secure uav communication with comp reception"):
  with members:
    - "efficient local map search algorithms for the placement of flying relays"
    - "secrecy transmission in large scale uav enabled wireless networks"
    - "cognitive uav communication via joint maneuver and power control"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "comp in the sky uav placement and movement optimization for multi user communications"
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "securing uav communications via joint trajectory and power control"

Connected through hyperedge HE-3 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach"):
  with members:
    - "a tutorial on beam management for 3gpp nr at mmwave frequencies"
    - "underlay drone cell for temporary events impact of drone height and aerial channel environments"
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "a stochastic model for uav networks positioned above demand hotspots in urban environments"
    - "coverage and connectivity analysis of millimeter wave vehicular networks"
    - "modeling and analyzing millimeter wave cellular systems"
    - "massive mimo for communications with drone swarms"
    - "backhaul for low altitude uavs in urban environments"

Connected through hyperedge HE-4 (induced by source paper "3d uav trajectory and communication design for simultaneous uplink and downlink transmission"):
  with members:
    - "energy efficient cooperative secure transmission in multi uav enabled wireless networks"
    - "throughput maximization for full duplex uav aided small cell wireless systems"
    - "3d trajectory optimization in rician fading for uav enabled data harvesting"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "uav aided offloading for cellular hotspot"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "securing uav communications via joint trajectory and power control"
    - "joint trajectory and communication design for multi uav enabled wireless networks"

Connected through hyperedge HE-5 (induced by source paper "online maneuver design for uav enabled noma systems via reinforcement learning"):
  with members:
    - "fundamental rate limits of uav enabled multiple access channel with trajectory optimization"
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "path design for cellular connected uav with reinforcement learning"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "deep learning in physical layer communications"
    - "placement optimization of uav mounted mobile base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"

Connected through hyperedge HE-6 (induced by source paper "a double q learning approach for navigation of aerial vehicles with connectivity constraint"):
  with members:
    - "trajectory design for cellular connected uav under outage duration constraint"
    - "efficient 3d aerial base station placement considering users mobility by reinforcement learning"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "the new frontier in ran heterogeneity multi tier drone cells"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "deep reinforcement learning with double q learning"

Connected through hyperedge HE-7 (induced by source paper "simulation of real time routing for uas traffic management with communication and airspace safety considerations"):
  with members:
    - "cellular connectivity for uavs network modeling performance analysis and design guidelines"
    - "a simulation framework for fast design space exploration of unmanned air system traffic management policies"

Connected through hyperedge HE-8 (induced by source paper "common throughput maximization for uav enabled interference channel with wireless powered communications"):
  with members:
    - "uav communications for 5g and beyond recent advances and future trends"
    - "fundamentals of wireless information and power transfer from rf energy harvester models to signal and system designs"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "optimal 1d trajectory design for uav enabled multiuser wireless power transfer"
    - "minimum throughput maximization in uav aided wireless powered communication networks"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "uav enabled wireless power transfer with directional antenna a two user case"
    - "throughput maximization for uav enabled wireless powered communication networks"

Question: Please tell me which class the center node 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)