Version 1
: Received: 15 August 2024 / Approved: 16 August 2024 / Online: 21 August 2024 (08:34:46 CEST)
Version 2
: Received: 18 September 2024 / Approved: 18 September 2024 / Online: 19 September 2024 (03:41:06 CEST)
How to cite:
He, H.; Zhou, C.; Huang, F.; Shen, H.; Yang, Y.; Liang, S. User-Cooperative Dynamic Resource Allocation for Backscatter-Aided Wireless-Powered MEC Network. Preprints2024, 2024081532. https://doi.org/10.20944/preprints202408.1532.v2
He, H.; Zhou, C.; Huang, F.; Shen, H.; Yang, Y.; Liang, S. User-Cooperative Dynamic Resource Allocation for Backscatter-Aided Wireless-Powered MEC Network. Preprints 2024, 2024081532. https://doi.org/10.20944/preprints202408.1532.v2
He, H., Yihong Yang and Shangsong Liang. 2024 "User-Cooperative Dynamic Resource Allocation for Backscatter-Aided Wireless-Powered MEC Network" Preprints. https://doi.org/10.20944/preprints202408.1532.v2
Abstract
Backscatter communication, which transmits information by passively reflecting radio frequency (RF) signals, has become a focal point of interest due to its potential to significantly enhance the energy efficiency of Wireless Power Mobile Edge Computing (WPMEC) networks and extend the operational lifespan of terminal devices. However, there is little research on the integration of user cooperation in WPMEC scenarios within volatile network environments. In this paper, we propose a dynamic task offloading scheme for a Backscatter-assisted WPMEC system, which involves two mobile devices (MDs) and a Hybrid Access Point (HAP) with user cooperation. We formulate the energy efficiency (EE) maximization problem as a stochastic programming problem, considering the randomness of task arrivals and time-varying wireless channels. By leveraging Dinkelbach’s method and stochastic network optimization technique, we transform the problem into a series of deterministic sub-problems for each time slot, and convert the non-convex sub-problem into convex ones. We propose a low-complex EE maximization algorithm to solve the convex problems efficiently. Extensive simulations are conducted to validate the performance of our algorithm under various system parameter settings. Experiment results demonstrate that our algorithm not only outperforms the benchmark algorithms by approximately 23%, but also stabilize all queues within the MEC system.
Keywords
Mobile edge computing (MEC); Wireless Power Transfer (WPT); User Cooperation (UC); backscatter communication (Backcom); Lyapunov optimization
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.