TY - JOUR
T1 - UAV Location Optimization in MISO ZF Pre-coded VLC Networks
AU - Eltokhey, Mahmoud Wafik
AU - Khalighi, Mohammad-Ali
AU - Ghassemlooy, Zabih
N1 - Funding information: This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 764461 (VisIoN), and was based upon work from European Union’s Horizon 2020 COST Action CA19111 (NEWFOCUS).
PY - 2022/1
Y1 - 2022/1
N2 - Use of unmanned aerial vehicles (UAVs) to provide on-demand communications has been receiving growing interest, especially for use in remote and hard-to-reach areas. Also, the use of light-emitting diode -based lighting in UAVs has opened opportunities for data transmission through visible-light communications. To manage multi-user interference while avoiding complex handover procedures, we consider the use of zero forcing (ZF) pre-coding. Since the performance of ZF pre-coding depends on the correlation between channel gains of users, we propose in this paper to reduce it by means of location optimization of UAVs. More specifically, we use particle swarm optimization with the objective of maximizing the overall achievable network throughput. Furthermore, to relax the optimization requirements at UAVs, we investigate the case when the optimization is performed at a specific rate under different mobility conditions.
AB - Use of unmanned aerial vehicles (UAVs) to provide on-demand communications has been receiving growing interest, especially for use in remote and hard-to-reach areas. Also, the use of light-emitting diode -based lighting in UAVs has opened opportunities for data transmission through visible-light communications. To manage multi-user interference while avoiding complex handover procedures, we consider the use of zero forcing (ZF) pre-coding. Since the performance of ZF pre-coding depends on the correlation between channel gains of users, we propose in this paper to reduce it by means of location optimization of UAVs. More specifically, we use particle swarm optimization with the objective of maximizing the overall achievable network throughput. Furthermore, to relax the optimization requirements at UAVs, we investigate the case when the optimization is performed at a specific rate under different mobility conditions.
KW - Correlation
KW - Interference
KW - Light emitting diodes
KW - Lighting
KW - MISO communication
KW - Optimization
KW - Particle swarm optimization
KW - ZF pre-coding
KW - unmanned-aerial vehicles
KW - Visible-light communications
UR - http://www.scopus.com/inward/record.url?scp=85117269288&partnerID=8YFLogxK
U2 - 10.1109/LWC.2021.3119221
DO - 10.1109/LWC.2021.3119221
M3 - Article
AN - SCOPUS:85117269288
SN - 2162-2337
VL - 11
SP - 28
EP - 32
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
IS - 1
ER -