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Randomization Approaches for Reducing PAPR with Partial Transmit Sequence and Semidefinite Relaxation
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Summary :
To reduce peak-to-average power ratio, we propose a method of choosing suitable vectors in a partial transmit sequence technique. Conventional approaches require that a suitable vector be selected from a large number of candidates. By contrast, our method does not include such a selecting procedure, and instead generates random vectors from the Gaussian distribution whose covariance matrix is a solution of a relaxed problem. The suitable vector is chosen from the random vectors. This yields lower peak-to-average power ratio than a conventional method.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E104-B No.3 pp.262-276
- Publication Date
- 2021/03/01
- Publicized
- 2020/09/01
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2019EBP3243
- Type of Manuscript
- PAPER
- Category
- Transmission Systems and Transmission Equipment for Communications
Authors
Hirofumi TSUDA
T&S inc.
Ken UMENO
the Kyoto University
Keyword
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Hirofumi TSUDA, Ken UMENO, "Randomization Approaches for Reducing PAPR with Partial Transmit Sequence and Semidefinite Relaxation" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 3, pp. 262-276, March 2021, doi: 10.1587/transcom.2019EBP3243.
Abstract: To reduce peak-to-average power ratio, we propose a method of choosing suitable vectors in a partial transmit sequence technique. Conventional approaches require that a suitable vector be selected from a large number of candidates. By contrast, our method does not include such a selecting procedure, and instead generates random vectors from the Gaussian distribution whose covariance matrix is a solution of a relaxed problem. The suitable vector is chosen from the random vectors. This yields lower peak-to-average power ratio than a conventional method.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2019EBP3243/_p
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@ARTICLE{e104-b_3_262,
author={Hirofumi TSUDA, Ken UMENO, },
journal={IEICE TRANSACTIONS on Communications},
title={Randomization Approaches for Reducing PAPR with Partial Transmit Sequence and Semidefinite Relaxation},
year={2021},
volume={E104-B},
number={3},
pages={262-276},
abstract={To reduce peak-to-average power ratio, we propose a method of choosing suitable vectors in a partial transmit sequence technique. Conventional approaches require that a suitable vector be selected from a large number of candidates. By contrast, our method does not include such a selecting procedure, and instead generates random vectors from the Gaussian distribution whose covariance matrix is a solution of a relaxed problem. The suitable vector is chosen from the random vectors. This yields lower peak-to-average power ratio than a conventional method.},
keywords={},
doi={10.1587/transcom.2019EBP3243},
ISSN={1745-1345},
month={March},}
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TY - JOUR
TI - Randomization Approaches for Reducing PAPR with Partial Transmit Sequence and Semidefinite Relaxation
T2 - IEICE TRANSACTIONS on Communications
SP - 262
EP - 276
AU - Hirofumi TSUDA
AU - Ken UMENO
PY - 2021
DO - 10.1587/transcom.2019EBP3243
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2021
AB - To reduce peak-to-average power ratio, we propose a method of choosing suitable vectors in a partial transmit sequence technique. Conventional approaches require that a suitable vector be selected from a large number of candidates. By contrast, our method does not include such a selecting procedure, and instead generates random vectors from the Gaussian distribution whose covariance matrix is a solution of a relaxed problem. The suitable vector is chosen from the random vectors. This yields lower peak-to-average power ratio than a conventional method.
ER -
English
