1.
Huang, Yi; Chen, Xiaofeng; Shen, Wei; Wei, Ziyi; Hu, Chengyong; Deng, Chuanlu; Wang, Lisen; Zhang, Qi; Chen, Wei; Zhang, Xiaobei; Chen, Lin; Jin, Wei; Tang, Jianming; Wang, Tingyun
Sidelobe Suppression Method with Improved CLEAN Algorithm for Pulse Compression OTDR Journal Article
In: IEEE Photonics Technology Letters, vol. 36, no. 22, pp. 1321–1324, 2024, ISSN: 1941-0174.
Abstract | Links | BibTeX | Tags: CLEAN algorithm, Encoding, Filtering, Optical fibers, Optical filters, Perturbation methods, phase coding, Pulse compression optical time domain reflectometry (PC-OTDR), sidelobe suppression, Signal to noise ratio, Spatial resolution
@article{huang_sidelobe_2024,
title = {Sidelobe Suppression Method with Improved CLEAN Algorithm for Pulse Compression OTDR},
author = {Yi Huang and Xiaofeng Chen and Wei Shen and Ziyi Wei and Chengyong Hu and Chuanlu Deng and Lisen Wang and Qi Zhang and Wei Chen and Xiaobei Zhang and Lin Chen and Wei Jin and Jianming Tang and Tingyun Wang},
url = {https://ieeexplore.ieee.org/document/10685474},
doi = {10.1109/LPT.2024.3465501},
issn = {1941-0174},
year = {2024},
date = {2024-11-01},
urldate = {2025-10-08},
journal = {IEEE Photonics Technology Letters},
volume = {36},
number = {22},
pages = {1321–1324},
abstract = {Although pulse compression optical time domain reflectometry (PC-OTDR) exhibits high performance in spatial resolution and dynamic range, it inevitably introduces auto-correlation sidelobes, potentially impacting measurement accuracy. In this letter, an improved CLEAN algorithm is proposed to efficiently suppress sidelobes and enhance the peak-to-sidelobe ratio (PSLR) of signals in PC-OTDR. The proposed method introduces an adaptive step factor instead of the traditional fixed factor to reduce the number of iterations. Compared to the traditional method, the proposed method achieves a 2.87 dB improvement of PSLR from a 10 km sensing fiber. In addition, the computation time cost is significantly reduced, which is 1.92 s less than that of the traditional CLEAN algorithm.},
keywords = {CLEAN algorithm, Encoding, Filtering, Optical fibers, Optical filters, Perturbation methods, phase coding, Pulse compression optical time domain reflectometry (PC-OTDR), sidelobe suppression, Signal to noise ratio, Spatial resolution},
pubstate = {published},
tppubtype = {article}
}
Although pulse compression optical time domain reflectometry (PC-OTDR) exhibits high performance in spatial resolution and dynamic range, it inevitably introduces auto-correlation sidelobes, potentially impacting measurement accuracy. In this letter, an improved CLEAN algorithm is proposed to efficiently suppress sidelobes and enhance the peak-to-sidelobe ratio (PSLR) of signals in PC-OTDR. The proposed method introduces an adaptive step factor instead of the traditional fixed factor to reduce the number of iterations. Compared to the traditional method, the proposed method achieves a 2.87 dB improvement of PSLR from a 10 km sensing fiber. In addition, the computation time cost is significantly reduced, which is 1.92 s less than that of the traditional CLEAN algorithm.
2.
Winter, Samuel; Zhang, Yangyishi; Zheng, Gan; Hanzo, Lajos
A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing Journal Article
In: IEEE Wireless Communications Letters, vol. 13, no. 5, pp. 1225–1229, 2024, ISSN: 2162-2345.
Abstract | Links | BibTeX | Tags: Annealing, downlink precoding, Hardware, Lattices, MIMO, Perturbation methods, Quantum annealing, Qubit, Symbols, vector perturbation
@article{winter_lattice-reduction_2024,
title = {A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing},
author = {Samuel Winter and Yangyishi Zhang and Gan Zheng and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10436537},
doi = {10.1109/LWC.2024.3365874},
issn = {2162-2345},
year = {2024},
date = {2024-05-01},
urldate = {2025-10-08},
journal = {IEEE Wireless Communications Letters},
volume = {13},
number = {5},
pages = {1225–1229},
abstract = {Quantum annealing (QA) is proposed for vector perturbation precoding (VPP) in multiple input multiple output (MIMO) communications systems. The mathematical framework of VPP is presented, outlining the problem formulation and the benefits of lattice reduction algorithms. Lattice reduction aided quantum vector perturbation (LRAQVP) is designed by harnessing physical quantum hardware, and the optimization of hardware parameters is discussed. We observe a 5dB gain over lattice reduction zero forcing precoding (LRZFP), which behaves similarly to a quantum annealing algorithm operating without a lattice reduction stage. The proposed algorithm is also shown to approach the performance of a sphere encoder, which exhibits an exponentially escalating complexity.},
keywords = {Annealing, downlink precoding, Hardware, Lattices, MIMO, Perturbation methods, Quantum annealing, Qubit, Symbols, vector perturbation},
pubstate = {published},
tppubtype = {article}
}
Quantum annealing (QA) is proposed for vector perturbation precoding (VPP) in multiple input multiple output (MIMO) communications systems. The mathematical framework of VPP is presented, outlining the problem formulation and the benefits of lattice reduction algorithms. Lattice reduction aided quantum vector perturbation (LRAQVP) is designed by harnessing physical quantum hardware, and the optimization of hardware parameters is discussed. We observe a 5dB gain over lattice reduction zero forcing precoding (LRZFP), which behaves similarly to a quantum annealing algorithm operating without a lattice reduction stage. The proposed algorithm is also shown to approach the performance of a sphere encoder, which exhibits an exponentially escalating complexity.