The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kertas kerja ini mencadangkan algoritma kelonggaran berlebihan (PSOR)-Jacobi berturut-turut secara berkala untuk pengesanan ralat min kuasa dua minimum (MMSE) bagi isyarat berbilang input berbilang keluaran (MIMO). Algoritma yang dicadangkan mempunyai kelebihan dua kaedah konvensional. Salah satunya ialah kaedah Jacobi, iaitu kaedah lelaran untuk menyelesaikan persamaan linear dan sesuai untuk pelaksanaan selari. Oleh itu, kaedah Jacobi adalah calon yang menjanjikan untuk penyelesai persamaan linear serentak berkelajuan tinggi untuk pengesan MMSE. Yang lain ialah kaedah Chebyshev PSOR, yang baru-baru ini telah ditunjukkan untuk mempercepatkan kelajuan penumpuan lelaran titik tetap linear. Kami membandingkan prestasi penumpuan algoritma PSOR-Jacobi dengan algoritma konvensional melalui simulasi komputer. Keputusan menunjukkan bahawa algoritma PSOR-Jacobi mencapai penumpuan yang lebih cepat tanpa meningkatkan kerumitan pengiraan, dan prestasi pengesanan yang lebih tinggi untuk bilangan lelaran tetap. Kertas ini juga mencadangkan kaedah pengiraan yang cekap bagi matriks songsang menggunakan algoritma PSOR-Jacobi. Keputusan simulasi komputer menunjukkan bahawa algoritma PSOR-Jacobi turut mempercepatkan pengiraan matriks songsang.
Asahi MIZUKOSHI
Nagoya Institute of Technology
Ayano NAKAI-KASAI
Nagoya Institute of Technology
Tadashi WADAYAMA
Nagoya Institute of Technology
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Salinan
Asahi MIZUKOSHI, Ayano NAKAI-KASAI, Tadashi WADAYAMA, "PSOR-Jacobi Algorithm for Accelerated MMSE MIMO Detection" in IEICE TRANSACTIONS on Fundamentals,
vol. E107-A, no. 3, pp. 486-492, March 2024, doi: 10.1587/transfun.2023TAP0004.
Abstract: This paper proposes the periodical successive over-relaxation (PSOR)-Jacobi algorithm for minimum mean squared error (MMSE) detection of multiple-input multiple-output (MIMO) signals. The proposed algorithm has the advantages of two conventional methods. One is the Jacobi method, which is an iterative method for solving linear equations and is suitable for parallel implementation. The Jacobi method is thus a promising candidate for high-speed simultaneous linear equation solvers for the MMSE detector. The other is the Chebyshev PSOR method, which has recently been shown to accelerate the convergence speed of linear fixed-point iterations. We compare the convergence performance of the PSOR-Jacobi algorithm with that of conventional algorithms via computer simulation. The results show that the PSOR-Jacobi algorithm achieves faster convergence without increasing computational complexity, and higher detection performance for a fixed number of iterations. This paper also proposes an efficient computation method of inverse matrices using the PSOR-Jacobi algorithm. The results of computer simulation show that the PSOR-Jacobi algorithm also accelerates the computation of inverse matrix.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2023TAP0004/_p
Salinan
@ARTICLE{e107-a_3_486,
author={Asahi MIZUKOSHI, Ayano NAKAI-KASAI, Tadashi WADAYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={PSOR-Jacobi Algorithm for Accelerated MMSE MIMO Detection},
year={2024},
volume={E107-A},
number={3},
pages={486-492},
abstract={This paper proposes the periodical successive over-relaxation (PSOR)-Jacobi algorithm for minimum mean squared error (MMSE) detection of multiple-input multiple-output (MIMO) signals. The proposed algorithm has the advantages of two conventional methods. One is the Jacobi method, which is an iterative method for solving linear equations and is suitable for parallel implementation. The Jacobi method is thus a promising candidate for high-speed simultaneous linear equation solvers for the MMSE detector. The other is the Chebyshev PSOR method, which has recently been shown to accelerate the convergence speed of linear fixed-point iterations. We compare the convergence performance of the PSOR-Jacobi algorithm with that of conventional algorithms via computer simulation. The results show that the PSOR-Jacobi algorithm achieves faster convergence without increasing computational complexity, and higher detection performance for a fixed number of iterations. This paper also proposes an efficient computation method of inverse matrices using the PSOR-Jacobi algorithm. The results of computer simulation show that the PSOR-Jacobi algorithm also accelerates the computation of inverse matrix.},
keywords={},
doi={10.1587/transfun.2023TAP0004},
ISSN={1745-1337},
month={March},}
Salinan
TY - JOUR
TI - PSOR-Jacobi Algorithm for Accelerated MMSE MIMO Detection
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 486
EP - 492
AU - Asahi MIZUKOSHI
AU - Ayano NAKAI-KASAI
AU - Tadashi WADAYAMA
PY - 2024
DO - 10.1587/transfun.2023TAP0004
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E107-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2024
AB - This paper proposes the periodical successive over-relaxation (PSOR)-Jacobi algorithm for minimum mean squared error (MMSE) detection of multiple-input multiple-output (MIMO) signals. The proposed algorithm has the advantages of two conventional methods. One is the Jacobi method, which is an iterative method for solving linear equations and is suitable for parallel implementation. The Jacobi method is thus a promising candidate for high-speed simultaneous linear equation solvers for the MMSE detector. The other is the Chebyshev PSOR method, which has recently been shown to accelerate the convergence speed of linear fixed-point iterations. We compare the convergence performance of the PSOR-Jacobi algorithm with that of conventional algorithms via computer simulation. The results show that the PSOR-Jacobi algorithm achieves faster convergence without increasing computational complexity, and higher detection performance for a fixed number of iterations. This paper also proposes an efficient computation method of inverse matrices using the PSOR-Jacobi algorithm. The results of computer simulation show that the PSOR-Jacobi algorithm also accelerates the computation of inverse matrix.
ER -