Article (Scientific journals)
Joint optimization of UAV-IRS placement and resource allocation for wireless powered mobile edge computing networks
Ahmec, Manzoor; Alshahrani, Haya Mesfer; Alruwais, Nuha et al.
2023In Journal of King Saud University - Computer and Information Sciences, 35 (8), p. 101646
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Keywords :
MEC; UAV; IRS; Resource allocation; Energy efficiency optimization
Abstract :
[en] The rapid evolution of communication systems towards the next generation has led to an increased deployment of Internet of Things (IoT) devices for various real-time applications. However, these devices often face limitations in terms of processing power and battery life, which can hinder overall system performance. Additionally, applications such as augmented reality and surveillance require intensive computations within tight timeframes. This research focuses on investigating a mobile edge computing (MEC) network empowered by unmanned aerial vehicle intelligent reflecting surfaces (UAV-IRS) to enhance the computational energy efficiency of the system through optimized resource allocation. The MEC infrastructure incorporates the energy transfer circuit (ETC) and edge server (ES), co-located with the intelligent access point (AP). To eliminate interference between energy transfer and data transmission, a time-division multiple access method is utilized. In the first phase, the ETC wirelessly transfers power to low-power IoT devices, which efficiently harvest and store the received energy in their batteries. In the second phase, IoT devices employ the stored energy for local computing or offloading tasks. Furthermore, the presence of tall buildings may obstruct communication routes, impacting system functionality. To address these challenges, we propose an optimization framework that simultaneously considers time, power, phase shift design, and local computational resources. This joint optimization problem is non-convex and non-linear, making it NP-hard. To tackle this complexity, we decompose the problem into subproblems and solve them iteratively using a convex optimization toolbox like CVX. Through simulations, we demonstrate that our proposed optimization framework significantly improves 40.7% system performance compared to alternative approaches.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Ahmec, Manzoor
Alshahrani, Haya Mesfer
Alruwais, Nuha
Asiri, Mashael M.
Duhayyim, Mesfer Al
Khan, Wali Ullah ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
khurshaid, Tahir
Nauman, Ali
External co-authors :
yes
Language :
English
Title :
Joint optimization of UAV-IRS placement and resource allocation for wireless powered mobile edge computing networks
Alternative titles :
[en] Joint optimization of UAV-IRS placement and resource allocation for wireless powered mobile edge computing networks
Publication date :
19 July 2023
Journal title :
Journal of King Saud University - Computer and Information Sciences
ISSN :
2213-1248
Publisher :
Elsevier
Volume :
35
Issue :
8
Pages :
101646
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
Available on ORBilu :
since 23 August 2023

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