Citation

Lum, Hui Tian and Chong, Woon Shing and Lee, Ying Loong and Tee, Yee Kai and Sheraz, Muhammad and Chuah, Teong Chee and Ke, Feng (2026) Fair Resource Allocation for Energy-Efficient Wireless-Powered Backscatter Communications: A Swarm Intelligence Approach. Wireless Personal Communications, 146 (4). pp. 2283-2307. ISSN 0929-6212

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Abstract

Wireless-powered backscatter communication (WP-BC) networks have emerged as a transformative low-power technology for supporting the massive Internet of Things (IoT). By passively modulating and reflecting radio frequency (RF) signals received from power beacons (PBs), backscatter transmitters can convey data to their receivers without consuming external power. Despite various resource allocation schemes proposed for WP-BC networks, none have effectively addressed the critical issue of ensuring energy efficiency fairness among multiple backscatter devices. To address this gap, we propose a novel interference-aware resource allocation scheme designed to maximize the individual energy efficiency of backscatter devices in a fair manner. Our approach formulates a nonconvex joint optimization problem for reflection coefficient and transmit power allocation, aiming to maximize a proportional-fairness utility function of energy efficiency under energyharvesting constraints. To solve this complex optimization problem, we introduce a new resource allocation algorithm leveraging a swarm intelligence approach. We demonstrate through simulation results that our proposed scheme significantly outperforms existing baseline schemes, achieving superior energy efficiency and enhanced fairness as measured by Jain’s fairness index. This work provides a substantial advancement in the efficient and fair allocation of resources in WP-BC networks, paving the way for more sustainable and equitable IoT solutions.

Item Type:	Article
Uncontrolled Keywords:	Backscatter communications
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 May 2026 05:01
Last Modified:	04 May 2026 05:01
URII:	http://shdl.mmu.edu.my/id/eprint/15875

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