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: "joint optimization of a uav s trajectory and transmit power for covert communications"
  Abstract: This work considers covert communications in the context of unmanned aerial vehicle (UAV) networks, aiming to hide a UAV for transmitting critical information out of a scenario that is monitored and where communication is not allowed. Specifically, the UAV as a transmitter intends to transmit information to a legitimate receiver (Bob) covertly in order to avoid being detected by a warden (Willie) with location uncertainties at Bob and/or Willie. In order to enhance the considered covert communication performance, we prefer to jointly optimize the UAV's trajectory and transmit power in terms of maximizing the average covert transmission rate from the UAV to Bob subject to transmission outage constraint and covertness constraint. The formulated optimization problem is difficult to tackle directly due to the intractable constraints. As such, we first employ conservative approximation to transform a constraint into a deterministic form and then apply the first-order restrictive approximation to transform the optimization problem into a convex form. By applying the successive convex approximation (SCA) technique, an efficient iterative algorithm is developed to solve the optimization problem. Our examination shows that the developed joint trajectory and transmit power optimization scheme achieves significantly better covert communication performance as compared to a benchmark scheme.

Connected through hyperedge HE-1 (induced by source paper "latency minimized design of secure transmissions in uav aided communications"):
  with members:
    - "energy efficient cooperative secure transmission in multi uav enabled wireless networks"
    - "user association and path planning for uav aided mobile edge computing with energy restriction"
    - "securing uav communications via joint trajectory and power control"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"

Connected through hyperedge HE-2 (induced by source paper "pilot based channel estimation design in covert wireless communication"):
  with members:
    - "multi antenna covert communications in random wireless networks"
    - "low probability of detection communication opportunities and challenges"
    - "covert transmission with a self sustained relay"
    - "gaussian signalling for covert communications"
    - "achieving covert wireless communications using a full duplex receiver"
    - "multi hop routing in covert wireless networks"
    - "covert wireless communications with channel inversion power control in rayleigh fading"
    - "covert communication achieved by a greedy relay in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "covert wireless communication in presence of a multi antenna adversary and delay constraints"):
  with members:
    - "multi antenna covert communications in random wireless networks"
    - "low probability of detection communication opportunities and challenges"
    - "gaussian signalling for covert communications"
    - "achieving covert wireless communications using a full duplex receiver"
    - "covert wireless communications with channel inversion power control in rayleigh fading"
    - "fundamental limits of covert communication over mimo awgn channel"
    - "covert communication achieved by a greedy relay in wireless networks"
    - "covert communication in fading channels under channel uncertainty"

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)