Cellular-Connected UAVs Research Articles

The Dynamic Response of Dual Cellular-Connected UAVs for Random Real-Time Communication Requests from Multiple Hotspots: A Deep Reinforcement Learning Approach

It is gradually becoming popular to use multiple cellular-connected UAVs as inspectors to fulfill automatic surveillance and monitoring. However, in actual situations, UAVs should respond to several service requests from different hotspots, whilst the requests usually present randomness in the arrival time, data amount, and the concurrency. This paper proposes a dynamic dual-UAV response policy for multi-hotspot services based on single-agent deep Q-learning, where the UAVs controlled by a ground base station can be dispatched automatically to hotspots and then send videos back. First, this issue is formulated as an optimization problem, whose goal is to maximize the number of successfully served requests with the constraints of both the UAV’s energy limit and request waiting time. Second, a reward function based on service completion is designed to overcome the potential challenges posed by the delay reward. Finally, a simulation was conducted, comparing the conventional time priority algorithm and distance priority algorithm, respectively, to the proposed algorithm. The results illustrate that the proposed algorithm can achieve one more response than the others under different service densities, with the lowest failure number and appropriate average waiting time. This method can give a technical solution for the joint communication-and-control problem of multiple UAVs within complex situations.

Performance of Cellular-Connected UAV in Cell-Free Radio Access Network With Network-Assisted Full-Duplex

Performance of Cellular-Connected UAV in Cell-Free Radio Access Network With Network-Assisted Full-Duplex

Fuzzy Logic Based Handover Under Multi-Connectivity in Cellular-Connected UAV Communications

Fuzzy Logic Based Handover Under Multi-Connectivity in Cellular-Connected UAV Communications

Autonomous Navigation for Cellular-Connected UAV in Highly Dynamic Environments: A Deep Reinforcement Learning Approach

Autonomous Navigation for Cellular-Connected UAV in Highly Dynamic Environments: A Deep Reinforcement Learning Approach

Trajectory Design for Integrated Sensing and Communication Enabled by Cellular-Connected UAV

Trajectory Design for Integrated Sensing and Communication Enabled by Cellular-Connected UAV

CoMP Transmission in Downlink NOMA-Based Cellular-Connected UAV Networks

CoMP Transmission in Downlink NOMA-Based Cellular-Connected UAV Networks

Sensing-assisted accurate and fast beam management for cellular-connected mmWave UAV network

Sensing-assisted accurate and fast beam management for cellular-connected mmWave UAV network

A Subarray Selection Scheme for Cellular-Connected UAV With Conformal Phased Array Antenna

A Subarray Selection Scheme for Cellular-Connected UAV With Conformal Phased Array Antenna

Mobility Management for Cellular-Connected UAVs: Model-Based Versus Learning-Based Approaches for Service Availability

Mobility Management for Cellular-Connected UAVs: Model-Based Versus Learning-Based Approaches for Service Availability

Throughput Performance of Cellular-Connected UAV Coexisting with Terrestrial Users

Unmanned aerial vehicles (UAVs) have opened up various applications with significant socioeconomic benefits, but require reliable connectivity for control and data transmission. In situations where obstacles separate aerial vehicles and ground operators, the cellular network can be used to establish beyond the visual line of sight (BVLOS) communication links. However, the cellular network is designed to optimize terrestrial user performance, so investigating its connectivity performance for aerial users is crucial. This paper presents an investigation into the upper-bound throughput estimations of the cellular network based on practical RSS measurements for both aerial and terrestrial users occupying the network resources simultaneously, in a typical sub-urban environment in Malaysia. Actual measurements of received signal strength (RSS) were taken to quantify the throughput performance for each category of users. Results indicate that the cellular network is feasible as a communication link for UAVs at altitudes below 40[Formula: see text]m. However, the overall throughput performance degrades when aerial users are present, and the probability of aerial user arrival must be kept at a minimum level beyond this height. Despite this, the mean aerial throughput outperforms the terrestrial throughput below 40[Formula: see text]m.

Trajectory Optimization and Pick-up and Delivery Sequence Design for Cellular-Connected Cargo UAVs

Trajectory Optimization and Pick-up and Delivery Sequence Design for Cellular-Connected Cargo UAVs

Channel State Acquisition in Uplink NOMA for Cellular-Connected UAV: Exploitation of Doppler and Modulation Diversities

Channel State Acquisition in Uplink NOMA for Cellular-Connected UAV: Exploitation of Doppler and Modulation Diversities

Mobility Performance Analyses of Base Station Cooperation for Cooperation for Cellular-Connected UAV Networks

Mobility Performance Analyses of Base Station Cooperation for Cooperation for Cellular-Connected UAV Networks

Flight Direction-Based Handover in Cellular-Connected UAV Communications

Flight Direction-Based Handover in Cellular-Connected UAV Communications

3D Radio Map Reconstruction and Trajectory Optimization for Cellular-Connected UAVs

3D Radio Map Reconstruction and Trajectory Optimization for Cellular-Connected UAVs

Inter-Cell Interference Mitigation for Cellular-Connected UAVs Using MOSDS-DQN

Inter-Cell Interference Mitigation for Cellular-Connected UAVs Using MOSDS-DQN

Uplink CoMP Transmission for Cellular-Connected UAV Networks

In this letter, we study the coordinated multipoint (CoMP) scheme in the uplink cellular-connected UAV network. By considering the LoS and NLoS components in air-to-ground (A2G) transmission, we adopt the strongest average received signal strength (RSS)-based CoMP scheme. We then develop an analytical framework to evaluate the network performance in terms of coverage probability and area spectral efficiency (ASE) for the case of two cooperative base stations (BSs), followed by an extension to a generalized number of cooperative BSs. Compared to the CoMP scheme with single UAV tier and Non-CoMP baseline, the considered CoMP scheme is able to leverage favored Line-of-Sight (LoS) transmission, lower path loss and BS cooperation gain.

Rate Meta Distribution of Downlink Base Station Cooperation for Cellular-Connected UAV Networks

This letter studies the downlink rate meta distribution of a typical UAV under base station (BS) cooperation in a cellular-connected UAV network. An analytical model is derived for the meta distribution of the downlink transmission rate of a typical UAV by using a standard beta distribution approximation, taking into account the LoS probability and Nakagami-m fading of a downlink. Based on the derived model, the impacts of relevant parameters on the rate meta distribution are investigated. The derived analytical model can be used to provide a reference for the setting of relevant parameters in the design of a BS cooperation strategy.

Mobility State Detection of Cellular-Connected UAVs Based on Handover Count Statistics

Mobility State Detection of Cellular-Connected UAVs Based on Handover Count Statistics

3D Radio Map-Based GPS Spoofing Detection and Mitigation for Cellular-Connected UAVs

3D Radio Map-Based GPS Spoofing Detection and Mitigation for Cellular-Connected UAVs