Energy-Efficient Resource Allocation for Backscatter-Assisted Wireless Powered MEC

Page view(s)
0
Checked on
Energy-Efficient Resource Allocation for Backscatter-Assisted Wireless Powered MEC
Title:
Energy-Efficient Resource Allocation for Backscatter-Assisted Wireless Powered MEC
Journal Title:
IEEE Transactions on Vehicular Technology
Publication Date:
17 July 2023
Citation:
Shi, L., Ye, Y., Chu, X., Sun, S., & Lu, G. (2023). Energy-Efficient resource allocation for Backscatter-Assisted Wireless powered MEC. IEEE Transactions on Vehicular Technology, 72(7), 9591–9596. https://doi.org/10.1109/tvt.2023.3246237
Abstract:
In this paper, we study the energy-efficient resource allocation for a backscatter-assisted wireless powered mobile edge computing (MEC) network. Considering the binary offloading mode and the limited computation capacity of the MEC server, we propose to minimize the MEC server's energy consumption by jointly optimizing the binary offloading decision of each IoT node, the computing frequencies and time at the MEC server and IoT nodes, the backscatter time and reflection coefficients of IoT nodes, as well as the MEC server's transmit power and time. It is formulated into a non-convex mixed integer programming problem. To solve this problem, we first obtain the optimal computing time and frequency for the MEC server and the optimal computing time of each IoT node based on the proof by contradiction and the monotonicity of the objective function, then we decouple the resulting simplified problem into two subproblems and transform each subproblem into a convex one. On this basis, we propose a low-complexity iterative algorithm to solve the simplified problem by solving the two convex subproblems alternately. Simulation results verify the fast convergence of the proposed iterative algorithm and its superiority over the baseline schemes in terms of the MEC server's energy consumption.
License type:
Publisher Copyright
Funding Info:
This research is supported by core funding from: A*STAR Institute for Infocomm Research (A*STAR I²R)
Grant Reference no. : NA
Description:
© 2023 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
ISSN:
0018-9545
1939-9359
Files uploaded:

File Size Format Action
4.pdf 452.79 KB PDF Open