TY - GEN
T1 - Unmanned aerial vehicle positioning and user equipment power allocation
AU - Martins, João
AU - Antunes, Carlos Henggeler
AU - Gomes, Marco
AU - Silva, Vitor
AU - Dinis, Rui
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PT#
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50008%2F2020/PT#
This work is funded by FCT/MEC through national funds and when applicable co-funded by European Regional Development Fund (FEDER), the Competitiveness and Internationalization Operational Programme (COMPETE 2020) of the Portugal 2020 framework, Regional OP Centro (POCI-01-0145-FEDER-030588) and Regional Operational Program of Lisbon (Lisboa-01-0145-FEDER-030588) and Financial Support National Public (FCT)(OE), under the projects UIBD/00308/2020, and the PhD SFRH/BD/08221/2021.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In the near future, unmanned aerial vehicles (UAVs) will have enormous potential applications for next generation wireless communication systems, in which they can collaborate to serve several user equipment (UE) for communication purposes. Disaster scenarios are a relevant research topic, in which UAVs can aid establishing connections in circumstances where base stations (BS) may be inoperative. The resulting UAV positioning affects the overall spectral efficiency (SE) in each UAV-UE link. Moreover, UEs energy consumption must be optimized since the finite amount of energy available is one of the most significant limitations of these devices. Therefore, it is essential to determine the lowest power consumption necessary to guarantee a minimum SE throughput in a disaster location. In this paper, we investigate a cooperative meta-heuristic (MH) optimization algorithm for both the UAVs and UEs. We propose two parallel optimization approaches: one is the UAV search position process to find the best possible location to serve its pre-allocated UEs; the other is finding the lowest possible uplink (UL) power values for each user's equipment. The preliminary results show that the Differential Evolution (DE) algorithm reaches good quality solutions in acceptable computation runtime.
AB - In the near future, unmanned aerial vehicles (UAVs) will have enormous potential applications for next generation wireless communication systems, in which they can collaborate to serve several user equipment (UE) for communication purposes. Disaster scenarios are a relevant research topic, in which UAVs can aid establishing connections in circumstances where base stations (BS) may be inoperative. The resulting UAV positioning affects the overall spectral efficiency (SE) in each UAV-UE link. Moreover, UEs energy consumption must be optimized since the finite amount of energy available is one of the most significant limitations of these devices. Therefore, it is essential to determine the lowest power consumption necessary to guarantee a minimum SE throughput in a disaster location. In this paper, we investigate a cooperative meta-heuristic (MH) optimization algorithm for both the UAVs and UEs. We propose two parallel optimization approaches: one is the UAV search position process to find the best possible location to serve its pre-allocated UEs; the other is finding the lowest possible uplink (UL) power values for each user's equipment. The preliminary results show that the Differential Evolution (DE) algorithm reaches good quality solutions in acceptable computation runtime.
KW - Differential Evolution (DE)
KW - Meta-heuristics (MHs)
KW - Position optimization
KW - Power allocation
KW - Unmanned aerial vehicle (UAV)
UR - http://www.scopus.com/inward/record.url?scp=85140440820&partnerID=8YFLogxK
U2 - 10.1109/CSNDSP54353.2022.9907929
DO - 10.1109/CSNDSP54353.2022.9907929
M3 - Conference contribution
AN - SCOPUS:85140440820
SN - 978-1-6654-1045-8
T3 - 2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2022
SP - 773
EP - 778
BT - 2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2022
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - New Jersey
T2 - 13th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2022
Y2 - 20 July 2022 through 22 July 2022
ER -