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: "comparison of limited feedback schemes for noma transmission in mmwave drone networks"
  Abstract: Introducing non-orthogonal multiple access (NOMA) transmission to an unmanned aerial vehicle (UAV) based communication network is a promising solution to enhance its spectral efficiency. However, for realistic deployment of such a network, identifying a practical user feedback scheme for NOMA is essential. In this paper, considering two practical feedback schemes we introduce NOMA transmission to UAVs acting as aerial base stations (BS) to provide coverage at a large stadium. In particular, a UAV-BS generates directional beams, and multiple users are served simultaneously within the same beam employing NOMA transmission. Each user is considered to have a target rate based on its quality of service (QoS) requirements. In order to relieve the burden of tracking and feeding back full channel state information, we consider two limited feedback schemes as practical alternatives: 1) user distance, and 2) user angle with respect to beamforming direction under different user region geometries. Our evaluation results show that NOMA with limited feedback can provide better sum rates compared to its orthogonal counterpart. Further, based on the geometry of user region we identify that there is an optimal feedback scheme and user ordering criteria for NOMA transmission which can maximize sum rates.

Connected through hyperedge HE-1 (induced by source paper "uav communications for 5g and beyond recent advances and future trends"):
  with members:
    - "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"
    - "uav enabled communication using noma"

Connected through hyperedge HE-2 (induced by source paper "angle feedback for noma transmission in mmwave drone networks"):
  with members:
    - "non orthogonal multiple access for mmwave drone networks with limited feedback"
    - "uav enabled communication using noma"
    - "non orthogonal multiple access for mmwave drones with multi antenna transmission"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "millimeter wave channel modeling and cellular capacity evaluation"

Connected through hyperedge HE-3 (induced by source paper "enhancing physical layer security for noma transmission in mmwave drone networks"):
  with members:
    - "enhancing the physical layer security of non orthogonal multiple access in large scale networks"
    - "mobile edge computing via a uav mounted cloudlet optimization of bit allocation and path planning"
    - "enhancing secrecy with multi antenna transmission in wireless ad hoc 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)