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: "the new frontier in ran heterogeneity multi tier drone cells"
  Abstract: In cellular networks, the locations of the radio access network (RAN) elements are determined mainly based on the long-term traffic behaviour. However, when the random and hard-to-predict spatio-temporal distribution of the traffic (load,demand) does not fully match the fixed locations of the RAN elements (supply), some performance degradation becomes inevitable. The concept of multi-tier cells (heterogeneous networks, HetNets) has been introduced in 4G networks to alleviate this mismatch. However, as the traffic distribution deviates more and more from the long-term average, even the HetNet architecture will have difficulty in coping up with the erratic supply-demand mismatch, unless the RAN is grossly over-engineered (which is a financially non-viable solution). In this article, we study the opportunistic utilization of low-altitude unmanned aerial platforms equipped with base stations (BSs), i.e., drone-BSs, in 5G networks. In particular, we envisage a multi-tier drone-cell network complementing the terrestrial HetNets. The variety of equipment, and non-rigid placement options allow utilizing multitier drone-cell networks to serve diversified demands. Hence, drone-cells bring the supply to where the demand is, which sets new frontiers for the heterogeneity in 5G networks. We investigate the advancements promised by drone-cells, and discuss the challenges associated with their operation and management. We propose a drone-cell management framework (DMF) benefiting from the synergy among software defined networking (SDN), network functions virtualization (NFV), and cloud-computing. We demonstrate DMF mechanisms via a case study, and numerically show that it can reduce the cost of utilizing drone-cells in multitenancy cellular networks.

Connected through hyperedge HE-1 (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-2 (induced by source paper "distributed collaborative 3d deployment of uav base stations for on demand coverage"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "efficient 3d aerial base station placement considering users mobility by reinforcement learning"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "drone small cells in the clouds design deployment and performance analysis"

Connected through hyperedge HE-3 (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"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "efficient 3d aerial base station placement considering users mobility by reinforcement learning"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "deep reinforcement learning with double q learning"

Connected through hyperedge HE-4 (induced by source paper "a survey of rate optimal power domain noma schemes for enabling technologies of future wireless networks"):
  with members:
    - "generalized coordinated multipoint gcomp enabled noma outage capacity and power allocation"
    - "what role can noma play in massive mimo"
    - "uav data collection over noma backscatter networks uav altitude and trajectory optimization"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "when full duplex wireless meets non orthogonal multiple access opportunities and challenges"
    - "on optimizing vlc networks for downlink multi user transmission a survey"
    - "beam design and user scheduling for nonorthogonal multiple access with multiple antennas based on pareto optimality"
    - "spatial modulation assisted multi antenna non orthogonal multiple access"

Connected through hyperedge HE-5 (induced by source paper "uav communications for 5g and beyond recent advances and future trends"):
  with members:
    - "comparison of limited feedback schemes for noma transmission in mmwave drone networks"
    - "energy optimization for cellular connected multi uav mobile edge computing systems with multi access schemes"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "resource allocation for solar powered uav communication systems"
    - "cellular connected uav potentials challenges and promising technologies"
    - "real time optimal resource allocation for embedded uav communication systems"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "minimum throughput maximization in uav aided wireless powered communication networks"

Connected through hyperedge HE-6 (induced by source paper "unmanned aerial vehicles uavs a survey on civil applications and key research challenges"):
  with members:
    - "resource allocation for solar powered uav communication systems"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "indoor mobile coverage problem using uavs"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "wireless communication using unmanned aerial vehicles uavs optimal transport theory for hover time optimization"
    - "efficient 3d placement of a uav using particle swarm optimization"
    - "placement optimization of uav mounted mobile base stations"

Connected through hyperedge HE-7 (induced by source paper "on the 3 d placement of airborne base stations using tethered uavs"):
  with members:
    - "capacity and coverage enhancement using long endurance tethered airborne base stations"
    - "average peak age of information minimization in uav assisted iot networks"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "cellular connectivity for uavs network modeling performance analysis and design guidelines"
    - "cellular uav to uav communications"
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "post disaster 4g 5g network rehabilitation using drones solving battery and backhaul issues"

Connected through hyperedge HE-8 (induced by source paper "secrecy transmission in large scale uav enabled wireless networks"):
  with members:
    - "a survey of optimization approaches for wireless physical layer security"
    - "exploiting noma oma for multi uav communications in large scale networks"
    - "exploiting noma for uav communications in large scale cellular networks"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "securing uav communications via joint trajectory and power control"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "physical layer security in cache enabled cooperative small cell networks against randomly distributed eavesdroppers"

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.NI(Networking and Internet Architecture)