Performance Improvement of Ordered Successive Detection with Imperfect Channel Estimates for MIMO Systems

Anass BENJEBBOUR; Susumu YOSHIDA

Performance Improvement of Ordered Successive Detection with Imperfect Channel Estimates for MIMO Systems

Anass BENJEBBOUR, Susumu YOSHIDA

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Ordered successive MMSE detection (OSD) can achieve a good tradeoff between performance and complexity for multiple-input multiple-output (MIMO) wireless systems where different data streams are transmitted and received simultaneously over several equal number of transmit and receive antennas. However, over time-varying MIMO channels, the performance of OSD is degraded with realistic channel estimation. In this paper, we introduce two different approaches in order to improve the performance of OSD. First, we propose to improve the accuracy of the generated nulling weights by using a modified noise variance that takes into consideration the weights update lag error besides to the noise and channel estimation errors. Second, we introduce a new iteration approach in order to improve the decisions made by OSD on transmitted streams. The proposed iterative scheme, named as backward iterative detection, exploits the tentative decisions on lately detected streams in order to mainly improve the decision on the firstly detected stream that limits the overall performance. Simulation results of combining both approaches show significant performance improvements of OSD.

Publication: IEICE TRANSACTIONS on Communications Vol.E86-B No.11 pp.3200-3208

Publication Date: 2003/11/01

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Type of Manuscript: PAPER

Category: Wireless Communication Technology

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Anass BENJEBBOUR, Susumu YOSHIDA, "Performance Improvement of Ordered Successive Detection with Imperfect Channel Estimates for MIMO Systems" in IEICE TRANSACTIONS on Communications, vol. E86-B, no. 11, pp. 3200-3208, November 2003, doi: .
Abstract: Ordered successive MMSE detection (OSD) can achieve a good tradeoff between performance and complexity for multiple-input multiple-output (MIMO) wireless systems where different data streams are transmitted and received simultaneously over several equal number of transmit and receive antennas. However, over time-varying MIMO channels, the performance of OSD is degraded with realistic channel estimation. In this paper, we introduce two different approaches in order to improve the performance of OSD. First, we propose to improve the accuracy of the generated nulling weights by using a modified noise variance that takes into consideration the weights update lag error besides to the noise and channel estimation errors. Second, we introduce a new iteration approach in order to improve the decisions made by OSD on transmitted streams. The proposed iterative scheme, named as backward iterative detection, exploits the tentative decisions on lately detected streams in order to mainly improve the decision on the firstly detected stream that limits the overall performance. Simulation results of combining both approaches show significant performance improvements of OSD.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e86-b_11_3200/_p

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@ARTICLE{e86-b_11_3200,
author={Anass BENJEBBOUR, Susumu YOSHIDA, },
journal={IEICE TRANSACTIONS on Communications},
title={Performance Improvement of Ordered Successive Detection with Imperfect Channel Estimates for MIMO Systems},
year={2003},
volume={E86-B},
number={11},
pages={3200-3208},
abstract={Ordered successive MMSE detection (OSD) can achieve a good tradeoff between performance and complexity for multiple-input multiple-output (MIMO) wireless systems where different data streams are transmitted and received simultaneously over several equal number of transmit and receive antennas. However, over time-varying MIMO channels, the performance of OSD is degraded with realistic channel estimation. In this paper, we introduce two different approaches in order to improve the performance of OSD. First, we propose to improve the accuracy of the generated nulling weights by using a modified noise variance that takes into consideration the weights update lag error besides to the noise and channel estimation errors. Second, we introduce a new iteration approach in order to improve the decisions made by OSD on transmitted streams. The proposed iterative scheme, named as backward iterative detection, exploits the tentative decisions on lately detected streams in order to mainly improve the decision on the firstly detected stream that limits the overall performance. Simulation results of combining both approaches show significant performance improvements of OSD.},
keywords={},
doi={},
ISSN={},
month={November},}

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TY - JOUR
TI - Performance Improvement of Ordered Successive Detection with Imperfect Channel Estimates for MIMO Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 3200
EP - 3208
AU - Anass BENJEBBOUR
AU - Susumu YOSHIDA
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E86-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2003
AB - Ordered successive MMSE detection (OSD) can achieve a good tradeoff between performance and complexity for multiple-input multiple-output (MIMO) wireless systems where different data streams are transmitted and received simultaneously over several equal number of transmit and receive antennas. However, over time-varying MIMO channels, the performance of OSD is degraded with realistic channel estimation. In this paper, we introduce two different approaches in order to improve the performance of OSD. First, we propose to improve the accuracy of the generated nulling weights by using a modified noise variance that takes into consideration the weights update lag error besides to the noise and channel estimation errors. Second, we introduce a new iteration approach in order to improve the decisions made by OSD on transmitted streams. The proposed iterative scheme, named as backward iterative detection, exploits the tentative decisions on lately detected streams in order to mainly improve the decision on the firstly detected stream that limits the overall performance. Simulation results of combining both approaches show significant performance improvements of OSD.
ER -