TY - JOUR
T1 - Capacity Analysis of IRS-Based UAV Communications with Imperfect Phase Compensation
AU - Al-Jarrah, M.
AU - Alsusa, E.
AU - Al-Dweik, A.
AU - So, Daniel K.C.
N1 - Funding Information:
Manuscript received March 3, 2021; accepted March 27, 2021. Date of publication April 5, 2021; date of current version July 9, 2021. This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme through the Marie Sklodowska-Curie under Grant 812991. The work of A. Al-Dweik was supported by Khalifa University Competitive Internal Research Awards under Grant CIRA-2020-056. The associate editor coordinating the review of this article and approving it for publication was F. Shu. (Corresponding author: M. Al-Jarrah.) M. Al-Jarrah, E. Alsusa, and Daniel K. C. So are with the Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, U.K. (e-mail: [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 2012 IEEE.
PY - 2021/7
Y1 - 2021/7
N2 - This letter presents the capacity analysis of unmanned aerial vehicles (UAVs) communications supported by flying intelligent reflecting surfaces (IRSs). In the considered system, some of the UAVs are equipped with an IRS panel that applies certain phase-shifts to the incident waves before being reflected to the receiving UAV. In contrast to existing work, this letter considers the effect of imperfect phase knowledge on the system capacity, where the phase error is modeled as a von Mises random variable with parameter κ . Analytical results, corroborated by Monte Carlo simulations, show that the achievable capacity is dependent on the phase error, however, the capacity loss becomes negligible at high signal-to-noise ratio (SNR) and when κ ≥ 6.
AB - This letter presents the capacity analysis of unmanned aerial vehicles (UAVs) communications supported by flying intelligent reflecting surfaces (IRSs). In the considered system, some of the UAVs are equipped with an IRS panel that applies certain phase-shifts to the incident waves before being reflected to the receiving UAV. In contrast to existing work, this letter considers the effect of imperfect phase knowledge on the system capacity, where the phase error is modeled as a von Mises random variable with parameter κ . Analytical results, corroborated by Monte Carlo simulations, show that the achievable capacity is dependent on the phase error, however, the capacity loss becomes negligible at high signal-to-noise ratio (SNR) and when κ ≥ 6.
KW - capacity
KW - flying network
KW - imperfect phase compensation
KW - IRS
KW - UAV
KW - Wireless backhauling
UR - http://www.scopus.com/inward/record.url?scp=85103884217&partnerID=8YFLogxK
U2 - 10.1109/LWC.2021.3071059
DO - 10.1109/LWC.2021.3071059
M3 - Article
AN - SCOPUS:85103884217
SN - 2162-2337
VL - 10
SP - 1479
EP - 1483
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
IS - 7
M1 - 9395180
ER -