H. Hellaoui, B. Yang, T. Taleb and J. Manner, "Ahead-Me Coverage (AMC): On Maintaining Enhanced Mobile Network Coverage for UAVs," GLOBECOM 2022 - 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil, 2022, pp. 2975-2980, doi: 10.1109/GLOBECOM48099.2022.10000874
Ahead-Me Coverage (AMC) : on maintaining enhanced mobile network coverage for UAVs
|Author:||Hellaoui, Hamed1; Yang, Bin2; Taleb, Tarik3;|
1Communications and Networking Department, Aalto University, Finland
2School of Computer and Information Engineering, Chuzhou University, China
3Centre for Wireless Communications, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023051143536
|Publish Date:|| 2023-05-11
This paper proposes the concept of Ahead-Me Cov-erage (AMC) aiming to get the coverage of a cellular network ahead of the mobile users for maintaining enhanced Quality- of-Service (QoS) in cellular-connected unmanned aerial vehicle (UAV) networks. In such networks, each base station (BS) with an intelligent logic can automatically tilt the direction of its radio antennas based on the trajectory of UAV s. For this purpose, we first formulate AMC as an integer optimization problem for maximizing the minimum transmission rate of UAVs by jointly optimizing the angles of the different radio antenna, the resource allocation and the selection of the appropriate serving BS for the UAVs throughout their path. For this complex optimization problem, we then propose a solution based on Deep Reinforcement Learning (DRL) to solve it. Under this solution, we adopt a multi-heterogeneous agent-based approach (MHA-DRL) including two types of agents, namely the UAV agents and the BS agents. Each agent implements an Advantage Actor Critic (A2C) to learn optimal policies. Specifically, the BS agents aim to tilt their antennas to get ahead of the UAV s throughout their mobility, and the UAV agents target selecting the appropriate serving BSs along with resource allocation. Performance evaluations are presented to validate the effectiveness of the proposed approach.
|Pages:||2975 - 3980|
GLOBECOM 2022 - 2022 IEEE Global Communications Conference
IEEE Global Communications Conference
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported by the European Union’s Horizon 2020 Research and Innovation Program through the 5G!Drones Project under Grant No. 857031.
|EU Grant Number:||
(857031) 5G!Drones - Unmanned Aerial Vehicle Vertical Applications’ Trials Leveraging Advanced 5G Facilities
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