Sequentially Iterative Equalizer Based on Kalman Filtering and Smoothing for MIMO Systems under Frequency Selective Fading Channels
Summary :
This paper proposes a sequentially iterative equalizer based on Kalman filtering and smoothing (SIEKFS) for multiple-input multiple-output (MIMO) systems under frequency selective fading channels. In the proposed SIEKFS, an iteration consists of sequentially executed subiterations, and each subiteration performs equalization and detection procedures of the symbols transmitted from a specific transmit antenna. During this subiteration, all available observations for the transmission block are utilized in the equalization procedures. Furthermore, the entire soft estimate of the desired symbols to be detected does not participate in the equalization procedures of the desired symbols, i.e., the proposed SIEKFS performs input-by-input equalization procedures for a priori information nulling. Therefore, compared with the original iterative equalizer based on Kalman filtering and smoothing, which performs symbol-by-symbol equalization procedures, the proposed SIEKFS can also perform iterative equalization based on the Kalman framework and turbo principle, with a significant reduction in computation complexity. Simulation results verify that the proposed SIEKFS achieves suboptimum error performance as the size of the antenna configuration and the number of iterations increase.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E101-B No.3 pp.909-914
- Publication Date
- 2018/03/01
- Publicized
- 2017/09/19
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2017EBP3084
- Type of Manuscript
- PAPER
- Category
- Wireless Communication Technologies
Authors
Sangjoon PARK
Wonkwang University
Keyword
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Sangjoon PARK, "Sequentially Iterative Equalizer Based on Kalman Filtering and Smoothing for MIMO Systems under Frequency Selective Fading Channels" in IEICE TRANSACTIONS on Communications,
vol. E101-B, no. 3, pp. 909-914, March 2018, doi: 10.1587/transcom.2017EBP3084.
Abstract: This paper proposes a sequentially iterative equalizer based on Kalman filtering and smoothing (SIEKFS) for multiple-input multiple-output (MIMO) systems under frequency selective fading channels. In the proposed SIEKFS, an iteration consists of sequentially executed subiterations, and each subiteration performs equalization and detection procedures of the symbols transmitted from a specific transmit antenna. During this subiteration, all available observations for the transmission block are utilized in the equalization procedures. Furthermore, the entire soft estimate of the desired symbols to be detected does not participate in the equalization procedures of the desired symbols, i.e., the proposed SIEKFS performs input-by-input equalization procedures for a priori information nulling. Therefore, compared with the original iterative equalizer based on Kalman filtering and smoothing, which performs symbol-by-symbol equalization procedures, the proposed SIEKFS can also perform iterative equalization based on the Kalman framework and turbo principle, with a significant reduction in computation complexity. Simulation results verify that the proposed SIEKFS achieves suboptimum error performance as the size of the antenna configuration and the number of iterations increase.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2017EBP3084/_p
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@ARTICLE{e101-b_3_909,
author={Sangjoon PARK, },
journal={IEICE TRANSACTIONS on Communications},
title={Sequentially Iterative Equalizer Based on Kalman Filtering and Smoothing for MIMO Systems under Frequency Selective Fading Channels},
year={2018},
volume={E101-B},
number={3},
pages={909-914},
abstract={This paper proposes a sequentially iterative equalizer based on Kalman filtering and smoothing (SIEKFS) for multiple-input multiple-output (MIMO) systems under frequency selective fading channels. In the proposed SIEKFS, an iteration consists of sequentially executed subiterations, and each subiteration performs equalization and detection procedures of the symbols transmitted from a specific transmit antenna. During this subiteration, all available observations for the transmission block are utilized in the equalization procedures. Furthermore, the entire soft estimate of the desired symbols to be detected does not participate in the equalization procedures of the desired symbols, i.e., the proposed SIEKFS performs input-by-input equalization procedures for a priori information nulling. Therefore, compared with the original iterative equalizer based on Kalman filtering and smoothing, which performs symbol-by-symbol equalization procedures, the proposed SIEKFS can also perform iterative equalization based on the Kalman framework and turbo principle, with a significant reduction in computation complexity. Simulation results verify that the proposed SIEKFS achieves suboptimum error performance as the size of the antenna configuration and the number of iterations increase.},
keywords={},
doi={10.1587/transcom.2017EBP3084},
ISSN={1745-1345},
month={March},}
Copy
TY - JOUR
TI - Sequentially Iterative Equalizer Based on Kalman Filtering and Smoothing for MIMO Systems under Frequency Selective Fading Channels
T2 - IEICE TRANSACTIONS on Communications
SP - 909
EP - 914
AU - Sangjoon PARK
PY - 2018
DO - 10.1587/transcom.2017EBP3084
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2018
AB - This paper proposes a sequentially iterative equalizer based on Kalman filtering and smoothing (SIEKFS) for multiple-input multiple-output (MIMO) systems under frequency selective fading channels. In the proposed SIEKFS, an iteration consists of sequentially executed subiterations, and each subiteration performs equalization and detection procedures of the symbols transmitted from a specific transmit antenna. During this subiteration, all available observations for the transmission block are utilized in the equalization procedures. Furthermore, the entire soft estimate of the desired symbols to be detected does not participate in the equalization procedures of the desired symbols, i.e., the proposed SIEKFS performs input-by-input equalization procedures for a priori information nulling. Therefore, compared with the original iterative equalizer based on Kalman filtering and smoothing, which performs symbol-by-symbol equalization procedures, the proposed SIEKFS can also perform iterative equalization based on the Kalman framework and turbo principle, with a significant reduction in computation complexity. Simulation results verify that the proposed SIEKFS achieves suboptimum error performance as the size of the antenna configuration and the number of iterations increase.
ER -
English
