TY - GEN
T1 - D3QN-Based Trajectory and Handover Management for UAVs Co-existing with Terrestrial Users
AU - Deng, Yuhang
AU - Meer, Irshad A.
AU - Zhang, Shuai
AU - Ozger, Mustafa
AU - Cavdar, Cicek
N1 - Publisher Copyright:
© 2023 IFIP.
PY - 2023
Y1 - 2023
N2 - The ubiquitous cellular network is a strong candidate for providing UAVs’ wireless connectivity. Due to the maneuverability advantage and higher altitude, UAVs could have line-of-sight (LoS) connectivity with more base station (BS) candidates than terrestrial users. However, the LoS connectivity could also enhance the propagation of up-link interference caused by UAVs over co-existing terrestrial users. In addition, UAVs would perform more handovers than terrestrial users when moving due to the extensive overlap in the coverage areas of many BS candidates. The solution is to bypass the overlapping coverage areas by designing the UAVs’ trajectory and to reduce interference by optimizing radio resource allocation through handover management. This paper studies the joint optimization of a UAV’s trajectory design and handover management to minimize the weighted sum of three key performance indicators (KPIs): delay, up-link interference, and handover numbers. A dueling double deep Q-network (D3QN) based reinforcement learning algorithm is proposed to solve the optimization problem. Results show that the proposed approach can reduce the handover numbers by 90% and the interference by 18% at the cost of a small increment in transmission delay when compared with the benchmark scheme, which controls the UAV to move along the shortest path and perform handover based on received signal strength. Finally, we verify the advantage of introducing trajectory design, which can reduce the interference by 29% and eliminate the handover numbers by 33% when compared to the D3QN-based policy without trajectory design.
AB - The ubiquitous cellular network is a strong candidate for providing UAVs’ wireless connectivity. Due to the maneuverability advantage and higher altitude, UAVs could have line-of-sight (LoS) connectivity with more base station (BS) candidates than terrestrial users. However, the LoS connectivity could also enhance the propagation of up-link interference caused by UAVs over co-existing terrestrial users. In addition, UAVs would perform more handovers than terrestrial users when moving due to the extensive overlap in the coverage areas of many BS candidates. The solution is to bypass the overlapping coverage areas by designing the UAVs’ trajectory and to reduce interference by optimizing radio resource allocation through handover management. This paper studies the joint optimization of a UAV’s trajectory design and handover management to minimize the weighted sum of three key performance indicators (KPIs): delay, up-link interference, and handover numbers. A dueling double deep Q-network (D3QN) based reinforcement learning algorithm is proposed to solve the optimization problem. Results show that the proposed approach can reduce the handover numbers by 90% and the interference by 18% at the cost of a small increment in transmission delay when compared with the benchmark scheme, which controls the UAV to move along the shortest path and perform handover based on received signal strength. Finally, we verify the advantage of introducing trajectory design, which can reduce the interference by 29% and eliminate the handover numbers by 33% when compared to the D3QN-based policy without trajectory design.
KW - cellular-connected UAVs
KW - handover management
KW - machine learning
KW - radio resource allocation
KW - reinforcement learning
KW - trajectory design
UR - http://www.scopus.com/inward/record.url?scp=85180568021&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85180568021&partnerID=8YFLogxK
U2 - 10.23919/WiOpt58741.2023.10349832
DO - 10.23919/WiOpt58741.2023.10349832
M3 - Conference contribution
AN - SCOPUS:85180568021
T3 - Proceedings of the International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt
SP - 103
EP - 110
BT - 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023
Y2 - 24 August 2023 through 27 August 2023
ER -