Cognitive UAV Communication via Joint Maneuver and Power Control

Abstract

This paper investigates a new scenario of spectrum sharing between unmanned aerial vehicle (UAV) and terrestrial wireless communication, in which a cognitive/secondary UAV transmitter communicates with a ground secondary receiver (SR), in the presence of a number of primary terrestrial communication links that operate over the same frequency band. We exploit the UAV's mobility in three-dimensional (3D) space to improve its cognitive communication performance while controlling the co-channel interference at the primary receivers (PRs), such that the received interference power at each PR is below a prescribed threshold termed as interference temperature (IT). First, we consider the quasi-stationary UAV scenario, where the UAV is placed at a static location during each communication period of interest. In this case, we jointly optimize the UAV's 3D placement and power control to maximize the SR's achievable rate, subject to the UAV's altitude and transmit power constraints, as well as a set of IT constraints at the PRs to protect their communications. Next, we consider the mobile UAV scenario, in which the UAV is dispatched to fly from an initial location to a final location within a given task period. We propose an efficient algorithm to maximize the SR's average achievable rate over this period by jointly optimizing the UAV's 3D trajectory and power control, subject to the additional constraints on UAV's maximum flying speed and initial/final locations. Finally, numerical results are provided to evaluate the performance of the proposed designs for different scenarios, as compared to various benchmark schemes. It is shown that in the quasi-stationary scenario the UAV should be placed at its minimum altitude while in the mobile scenario the UAV should adjust its altitude along with horizontal trajectory, so as to maximize the SR's achievable rate in both scenarios.

arXiv comment16 pages,11 figures, accepted by IEEE Transactions on Communications

References in corpus (12)

• Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges
• Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage
• Placement Optimization of UAV-Mounted Mobile Base Stations
• The Sky Is Not the Limit: LTE for Unmanned Aerial Vehicles
• Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity
• 3D Placement of an Unmanned Aerial Vehicle Base Station for Maximum Coverage of Users with Different QoS Requirements
• Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management
• Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
• Uplink Cooperative NOMA for Cellular-Connected UAV
• An Overview of 3GPP Release-15 Study on Enhanced LTE Support for Connected Drones
• Placement Optimization for UAV-Enabled Wireless Networks with Multi-Hop Backhaul
• Trajectory Optimization for Completion Time Minimization in UAV-Enabled Multicasting

Cited by in corpus (10)

• Cache-enabling UAV Communications: Network Deployment and Resource Allocation
• Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach
• Fundamental Rate Limits of UAV-Enabled Multiple Access Channel with Trajectory Optimization
• Accessing From The Sky: A Tutorial on UAV Communications for 5G and Beyond
• Cellular-Connected UAV with Adaptive Air-to-Ground Interference Cancellation and Trajectory Optimization
• Radio Map Based 3D Path Planning for Cellular-Connected UAV
• Resource Allocation for Secure Multi-UAV Communication Systems with Multi-Eavesdropper
• Lifetime Maximization for UAV-Enabled Cognitive-NOMA IoT Networks: Joint Location, Power, and Decoding Order Optimization
• Robust Trajectory and Transmit Power Optimization for Secure UAV-Enabled Cognitive Radio Networks
• Joint 3D Maneuver and Power Adaptation for Secure UAV Communication with CoMP Reception