TY - GEN
T1 - Optimal Resource Allocation and Placement for Terrestrial and Aerial Base Stations in Mixed RF/FSO Backhaul Networks
AU - Lee, Ju Hyung
AU - Park, Ki Hong
AU - Alouini, Mohamed Slim
AU - Ko, Young Chai
N1 - Funding Information:
ACKNOWLEDGEMENT This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2020-2015-0-00385) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation).
Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - In this work, we address the optimization of vertical backhaul framework where multiple aerial base station (ABS) are deployed to conFigure the intermediate backhaul links for terrestrial base stations (TBS) in wireless networks. Here, we focus on maximizing the downlink network throughput in mixed RF/FSO backhaul networks by optimizing resource allocation and placement. Specifically, the ABS-TBS association, transmit power, and positions of ABSs are alternately and iteratively optimized. To solve the corresponding mixed-integer non-convex optimization problem, we propose an efficient iterative algorithm by applying the block coordinate descent method and successive convex optimization techniques. Although we obtain suboptimal solutions due to the non-convexity of the problems, simulation results indicate that the proposed scheme demonstrates the significant network throughput gain compared with the conventional scheme.
AB - In this work, we address the optimization of vertical backhaul framework where multiple aerial base station (ABS) are deployed to conFigure the intermediate backhaul links for terrestrial base stations (TBS) in wireless networks. Here, we focus on maximizing the downlink network throughput in mixed RF/FSO backhaul networks by optimizing resource allocation and placement. Specifically, the ABS-TBS association, transmit power, and positions of ABSs are alternately and iteratively optimized. To solve the corresponding mixed-integer non-convex optimization problem, we propose an efficient iterative algorithm by applying the block coordinate descent method and successive convex optimization techniques. Although we obtain suboptimal solutions due to the non-convexity of the problems, simulation results indicate that the proposed scheme demonstrates the significant network throughput gain compared with the conventional scheme.
UR - http://www.scopus.com/inward/record.url?scp=85088284841&partnerID=8YFLogxK
U2 - 10.1109/VTC2020-Spring48590.2020.9128939
DO - 10.1109/VTC2020-Spring48590.2020.9128939
M3 - Conference contribution
AN - SCOPUS:85088284841
T3 - IEEE Vehicular Technology Conference
BT - 2020 IEEE 91st Vehicular Technology Conference, VTC Spring 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 91st IEEE Vehicular Technology Conference, VTC Spring 2020
Y2 - 25 May 2020 through 28 May 2020
ER -