Joint Resource Allocation for Full-Duplex Ambient Backscatter Communication: A Difference Convex Algorithm

Nowadays, Ambient Backscatter Communication (AmBC) systems have emerged as a green communication technology to enable massive self-sustainable wireless networks by leveraging Radio Frequency (RF) Energy Harvesting (EH) capability. A Full-duplex Ambient Backscatter Communication (FAmBC) network with...

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Veröffentlicht in:IEEE transactions on wireless communications Jg. 21; H. 10; S. 8022 - 8035
Hauptverfasser: Madavani, Fatemeh Kaveh, Soleimanpour-Moghadam, Mohadeseh, Talebi, Siamak, Chatzinotas, Symeon, Ottersten, Bjorn
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Ambient backscatter communication
Backscatter
Backscattering
Communication
Computational geometry
Convexity
Difference Convex Programming
Energy harvesting
Multi-objective optimization problem
Multiple objective analysis
Non-convex problem
Optimization
Orthogonal Frequency Division Multiplexing
Penalty function
Radio frequency
Receivers
Resource allocation
Resource management
Throughput
Wireless communication
Wireless networks
Wireless-driven IoT
ISSN:1536-1276, 1558-2248, 1558-2248
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Zusammenfassung:Nowadays, Ambient Backscatter Communication (AmBC) systems have emerged as a green communication technology to enable massive self-sustainable wireless networks by leveraging Radio Frequency (RF) Energy Harvesting (EH) capability. A Full-duplex Ambient Backscatter Communication (FAmBC) network with a Full-duplex Access Point (AP), a dedicated Legacy User (LU), and several Backscatter Devices (BDs) is considered in this study. The AP with two antennas transfers downlink Orthogonal Frequency Division Multiplexing (OFDM) information and energy to the dedicated LU and several BDs, respectively, while receiving uplink backscattered information from BDs at the same time. One of the key aims in AmBC networks is to ensure fairness among BDs. To address this, we propose the Multi-objective Lexicographical Optimization Problem (MLOP), which aims to maximize the minimum BD's throughput while enhancing overall BDs' throughput, subject to the AP's subcarrier power, BDs' reflection coefficients, and backscatter time allocation. Owe to the MLOP is non-convex, we propose Difference Convex Algorithm (DCA) using Exterior Penalty Function Method (EPFM)-an inventive non-convex optimization method- to reach the optimal solution. The most critical advantage of applying this proposed approach is finding the globally optimal solution. The effectiveness of the proposed method supported by theoretical analysis confirms its superiority compared to some of the investigated suboptimal algorithms with the same computational complexity.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1536-1276
1558-2248
1558-2248
DOI:10.1109/TWC.2022.3163718