Robust resource allocation for wireless-powered backscatter communication systems with NOMA
The integration of wireless-powered communication and backscatter communication (BackCom) is envisioned as a promising communication paradigm for the future Internet of Things (IoT), where resource allocation (RA) as a critical technique can improve achievable capacity by dynamically adjusting syste...
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sg-ntu-dr.10356-1708092023-10-03T04:39:01Z Robust resource allocation for wireless-powered backscatter communication systems with NOMA Xu, Yongjun Xu, Ran Li, Dong Yang, Gang Wang, Gongpu Yuen, Chau Zhou, Jihua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Backscatter Communication Robust Resource Allocation The integration of wireless-powered communication and backscatter communication (BackCom) is envisioned as a promising communication paradigm for the future Internet of Things (IoT), where resource allocation (RA) as a critical technique can improve achievable capacity by dynamically adjusting system parameters (e.g., transmit power, beamforming vectors). However, the existing RA algorithms consider the ideal cases of perfect channel state information and linear energy harvesting (EH), which will deteriorate system performance. To fill this gap, in this paper, we investigate a robust RA problem for a wireless-powered BackCom system with non-orthogonal multiple access (NOMA) under the consideration of practical channel uncertainties and nonlinear EH models. The robust RA problem with Euclidean spherical uncertainties is formulated by optimizing the transmit beamforming vector of the access point (AP), the transmit power of each IoT device, and time allocation factors, where the maximum power constraint of the AP, the time frame constraint, the minimum EH constraint, and the quality of service constraint of each user are considered simultaneously. Subsequently, according to the block coordinate descent iterative method, an iteration-based robust RA algorithm is proposed by using the successive convex approximation, S-procedure, semidefinite relaxation, and Gaussian randomization methods. Simulation results prove that our proposed algorithm can drastically enhance system robustness compared to the non-robust algorithm and several benchmark algorithms. The work of Dong Li was supported by the Science and Technology Development Fund, Macau, China, under Grants 0018/2019/AMJ, 0110/2020/A3, and 0029/2021/AGJ. This work was supported in part by the National Natural Science Foundation of China under Grants 62271094, 62071093, and U21A20448, in part by the Scientific and Technological Research Program of Chongqing Municipal Education Commission under Grant KJZDK202200601, and in part by China Postdoctoral Science Foundation under Grant 2022MD723725. 2023-10-03T04:39:01Z 2023-10-03T04:39:01Z 2023 Journal Article Xu, Y., Xu, R., Li, D., Yang, G., Wang, G., Yuen, C. & Zhou, J. (2023). Robust resource allocation for wireless-powered backscatter communication systems with NOMA. IEEE Transactions On Vehicular Technology, 72(9), 12288-12299. https://dx.doi.org/10.1109/TVT.2023.3271106 0018-9545 https://hdl.handle.net/10356/170809 10.1109/TVT.2023.3271106 2-s2.0-85159690721 9 72 12288 12299 en IEEE Transactions on Vehicular Technology © 2023 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Backscatter Communication Robust Resource Allocation Xu, Yongjun Xu, Ran Li, Dong Yang, Gang Wang, Gongpu Yuen, Chau Zhou, Jihua Robust resource allocation for wireless-powered backscatter communication systems with NOMA |
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The integration of wireless-powered communication and backscatter communication (BackCom) is envisioned as a promising communication paradigm for the future Internet of Things (IoT), where resource allocation (RA) as a critical technique can improve achievable capacity by dynamically adjusting system parameters (e.g., transmit power, beamforming vectors). However, the existing RA algorithms consider the ideal cases of perfect channel state information and linear energy harvesting (EH), which will deteriorate system performance. To fill this gap, in this paper, we investigate a robust RA problem for a wireless-powered BackCom system with non-orthogonal multiple access (NOMA) under the consideration of practical channel uncertainties and nonlinear EH models. The robust RA problem with Euclidean spherical uncertainties is formulated by optimizing the transmit beamforming vector of the access point (AP), the transmit power of each IoT device, and time allocation factors, where the maximum power constraint of the AP, the time frame constraint, the minimum EH constraint, and the quality of service constraint of each user are considered simultaneously. Subsequently, according to the block coordinate descent iterative method, an iteration-based robust RA algorithm is proposed by using the successive convex approximation, S-procedure, semidefinite relaxation, and Gaussian randomization methods. Simulation results prove that our proposed algorithm can drastically enhance system robustness compared to the non-robust algorithm and several benchmark algorithms. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Xu, Yongjun Xu, Ran Li, Dong Yang, Gang Wang, Gongpu Yuen, Chau Zhou, Jihua |
format |
Article |
author |
Xu, Yongjun Xu, Ran Li, Dong Yang, Gang Wang, Gongpu Yuen, Chau Zhou, Jihua |
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Xu, Yongjun |
title |
Robust resource allocation for wireless-powered backscatter communication systems with NOMA |
title_short |
Robust resource allocation for wireless-powered backscatter communication systems with NOMA |
title_full |
Robust resource allocation for wireless-powered backscatter communication systems with NOMA |
title_fullStr |
Robust resource allocation for wireless-powered backscatter communication systems with NOMA |
title_full_unstemmed |
Robust resource allocation for wireless-powered backscatter communication systems with NOMA |
title_sort |
robust resource allocation for wireless-powered backscatter communication systems with noma |
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2023 |
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https://hdl.handle.net/10356/170809 |
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1779156686363164672 |