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Joint Altitude, Beamwidth, Location and Bandwidth Optimization for UAV-Enabled Communications
This letter investigates an uplink power control problem for unmanned ae...
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UAV Positioning and Power Control for Two-Way Wireless Relaying
This paper considers an unmanned-aerial-vehicle-enabled (UAV-enabled) wi...
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Power Control for a URLLC-enabled UAV system incorporated with DNN-Based Channel Estimation
This letter is concerned with power control for a ultra-reliable and low...
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Communications and Control for Wireless Drone-Based Antenna Array
In this paper, the effective use of multiple quadrotor drones as an aeri...
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Robust Resource Allocation for UAV Systems with UAV Jittering and User Location Uncertainty
In this paper, we investigate resource allocation algorithm design for m...
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Optimal Transmit Power and Flying Location for UAV Covert Wireless Communications
This paper jointly optimizes the flying location and wireless communicat...
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Online Trajectory Optimization for Rotary-Wing UAVs in Wireless Networks
This paper studies the trajectory optimization problem in an online sett...
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Joint Location and Power Optimization for THz-enabled UAV Communications
In this paper, the problem of unmanned aerial vehicle (UAV) deployment and power allocation is investigated for a UAV-assisted wireless system operating at terahertz (THz) frequencies. In the studied model, one UAV can service ground users using the THz frequency band. However, the highly uncertain THz channel will introduce new challenges to the UAV location and user power allocation optimization problems. Therefore, it is necessary to design a novel framework to deploy UAVs in the THz wireless systems. This problem is formally posed as an optimization problem whose goal is to minimize the sum uplink and downlink transmission delays between the UAV and the ground users by jointly optimizing the deployment of the UAV and the transmit power of the users. To tackle this nonconvex delay minimization problem, an alternating algorithm is proposed while iteratively solving two subproblems: location optimization subproblem and power control subproblem. Simulation results show that the proposed algorithm can reduce the transmission delay by up to 67.3% and 52.5% respectively compared to baseline algorithms that fix transmit power control or UAV location.
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