Joint Beamforming and Transmission Design for Hybrid Backscatter-HTT Communication System

Backscatter communication and harvest-then-transmit (HTT) communication are regarded as promising technologies for enabling green Internet of Things (IoT). The current works on the joint use of backscatter communication and HTT are limited in single cell scenarios with the fixed backscatter-then-HTT transmission structure. In this work, we propose a transmission scheme with flexible mode selection for the hybrid backscatter-HTT multi-cell system to achieve much improved communication performance, and then study the joint design for such a system. Specifically, by utilizing multi-antenna technology and enabling the flexible mode selecting between backscatter and HTT, a novel transmission scheme is developed. With the aim to maximize the sum rate of the considered system, we formulate a joint optimization problem for the base station transmission beamforming (TB), the transmission mode (TM), and the transmit power (TP) of the hybrid backscatter-HTT devices. To address the formulated non-convex problem, we propose a block coordinate descent-based algorithm, namely J3TO, to jointly optimize TB, TM, and TP, by decoupling the original problem into three sub-problems. Therein, the weighted minimum mean square error approach, matching theory, and the fractional programming technique are leveraged to deal with the sub-problems efficiently. Simulation results show that the proposed algorithm flexibly integrates the merits of backscatter and HTT technologies, achieving superior performance across various scenarios, compared with the benchmark schemes, e.g., backscatter-only SDMA, HTT-only SDMA, and backscatter-HTT TDMA.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-01-01
DOI
https://doi.org/10.1109/jiot.2025.3602056
Citations
1
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.73
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article

Joint Beamforming and Transmission Design for Hybrid Backscatter-HTT Communication System

Zesong Fei, Salman Durrani, Hanxiao Yu, Jing Guo et al.
1 citations
IEEE Internet of Things Journal
Energy Harvesting in Wireless Networks
0.73
article

Joint Beamforming and Transmission Design for Hybrid Backscatter-HTT Communication System

Zesong Fei, Salman Durrani, Hanxiao Yu, Jing Guo, Xiangyun Zhou, Xinyi Wang, Chenyang Du
article en
1 citations

Abstract

Backscatter communication and harvest-then-transmit (HTT) communication are regarded as promising technologies for enabling green Internet of Things (IoT). The current works on the joint use of backscatter communication and HTT are limited in single cell scenarios with the fixed backscatter-then-HTT transmission structure. In this work, we propose a transmission scheme with flexible mode selection for the hybrid backscatter-HTT multi-cell system to achieve much improved communication performance, and then study the joint design for such a system. Specifically, by utilizing multi-antenna technology and enabling the flexible mode selecting between backscatter and HTT, a novel transmission scheme is developed. With the aim to maximize the sum rate of the considered system, we formulate a joint optimization problem for the base station transmission beamforming (TB), the transmission mode (TM), and the transmit power (TP) of the hybrid backscatter-HTT devices. To address the formulated non-convex problem, we propose a block coordinate descent-based algorithm, namely J3TO, to jointly optimize TB, TM, and TP, by decoupling the original problem into three sub-problems. Therein, the weighted minimum mean square error approach, matching theory, and the fractional programming technique are leveraged to deal with the sub-problems efficiently. Simulation results show that the proposed algorithm flexibly integrates the merits of backscatter and HTT technologies, achieving superior performance across various scenarios, compared with the benchmark schemes, e.g., backscatter-only SDMA, HTT-only SDMA, and backscatter-HTT TDMA.

IEEE Internet of Things Journal
Australian National University (AU), Beijing Institute of Technology (CN), Institute of Computing Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 24%
Energy Harvesting in Wireless Networks
0.73
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