Joint estimation of channel and oscillator phase noise in MIMO systems

Hani Mehrpouyan; Ali A. Nasir; Steven D. Blostein; Thomas Eriksson; George K. Karagiannidis; Tommy Svensson

doi:10.1109/TSP.2012.2202652

Joint estimation of channel and oscillator phase noise in MIMO systems

Hani Mehrpouyan^*
, Ali A. Nasir
, Steven D. Blostein
, Thomas Eriksson
, George K. Karagiannidis
, Tommy Svensson

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

133 Scopus citations

Abstract

Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains and Wiener phase noise in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail and new expressions for the Cramér-Rao lower bounds (CRLBs) for the multi-parameter estimation problem are derived. A data-aided least-squares (LS) estimator for jointly obtaining the channel gains and phase noise parameters is derived. Next, a decision-directed weighted least-squares (WLS) estimator is proposed, where pilots and estimated data symbols are employed to track the time-varying phase noise parameters over a frame. In order to reduce the overhead and delay associated with the estimation process, a new decision-directed extended Kalman filter (EKF) is proposed for tracking the MIMO phase noise throughout a frame. Numerical results show that the proposed LS, WLS, and EKF estimators' performances are close to the CRLB. Finally, simulation results demonstrate that by employing the proposed channel and time-varying phase noise estimators the bit-error rate performance of a MIMO system can be significantly improved.

Original language	English
Article number	6212402
Pages (from-to)	4790-4807
Number of pages	18
Journal	IEEE Transactions on Signal Processing
Volume	60
Issue number	9
DOIs	https://doi.org/10.1109/TSP.2012.2202652
State	Published - 2012
Externally published	Yes

Bibliographical note

Funding Information:
Manuscript received July 18, 2011; revised February 21, 2012 and April 27, 2012; accepted May 25, 2012. Date of publication June 05, 2012; date of current version August 07, 2012. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ut-Va Koc. This work was supported by the Swedish Research Council, Vinnova, Ericsson AB, Qamcom Technology AB, and the International Ph.D. Scholarship.

Keywords

Channel estimation
Cramér-Rao lower bound (CRLB)
Wiener phase noise
extended Kalman filter (EKF)
multi-input multi-output (MIMO)
weighted least squares (WLS)

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

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10.1109/TSP.2012.2202652

Cite this

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title = "Joint estimation of channel and oscillator phase noise in MIMO systems",

abstract = "Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains and Wiener phase noise in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail and new expressions for the Cram{\'e}r-Rao lower bounds (CRLBs) for the multi-parameter estimation problem are derived. A data-aided least-squares (LS) estimator for jointly obtaining the channel gains and phase noise parameters is derived. Next, a decision-directed weighted least-squares (WLS) estimator is proposed, where pilots and estimated data symbols are employed to track the time-varying phase noise parameters over a frame. In order to reduce the overhead and delay associated with the estimation process, a new decision-directed extended Kalman filter (EKF) is proposed for tracking the MIMO phase noise throughout a frame. Numerical results show that the proposed LS, WLS, and EKF estimators' performances are close to the CRLB. Finally, simulation results demonstrate that by employing the proposed channel and time-varying phase noise estimators the bit-error rate performance of a MIMO system can be significantly improved.",

keywords = "Channel estimation, Cram{\'e}r-Rao lower bound (CRLB), Wiener phase noise, extended Kalman filter (EKF), multi-input multi-output (MIMO), weighted least squares (WLS)",

author = "Hani Mehrpouyan and Nasir, \{Ali A.\} and Blostein, \{Steven D.\} and Thomas Eriksson and Karagiannidis, \{George K.\} and Tommy Svensson",

note = "Funding Information: Manuscript received July 18, 2011; revised February 21, 2012 and April 27, 2012; accepted May 25, 2012. Date of publication June 05, 2012; date of current version August 07, 2012. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ut-Va Koc. This work was supported by the Swedish Research Council, Vinnova, Ericsson AB, Qamcom Technology AB, and the International Ph.D. Scholarship.",

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AU - Mehrpouyan, Hani

AU - Nasir, Ali A.

AU - Blostein, Steven D.

AU - Eriksson, Thomas

AU - Karagiannidis, George K.

AU - Svensson, Tommy

N1 - Funding Information: Manuscript received July 18, 2011; revised February 21, 2012 and April 27, 2012; accepted May 25, 2012. Date of publication June 05, 2012; date of current version August 07, 2012. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ut-Va Koc. This work was supported by the Swedish Research Council, Vinnova, Ericsson AB, Qamcom Technology AB, and the International Ph.D. Scholarship.

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N2 - Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains and Wiener phase noise in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail and new expressions for the Cramér-Rao lower bounds (CRLBs) for the multi-parameter estimation problem are derived. A data-aided least-squares (LS) estimator for jointly obtaining the channel gains and phase noise parameters is derived. Next, a decision-directed weighted least-squares (WLS) estimator is proposed, where pilots and estimated data symbols are employed to track the time-varying phase noise parameters over a frame. In order to reduce the overhead and delay associated with the estimation process, a new decision-directed extended Kalman filter (EKF) is proposed for tracking the MIMO phase noise throughout a frame. Numerical results show that the proposed LS, WLS, and EKF estimators' performances are close to the CRLB. Finally, simulation results demonstrate that by employing the proposed channel and time-varying phase noise estimators the bit-error rate performance of a MIMO system can be significantly improved.

AB - Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains and Wiener phase noise in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail and new expressions for the Cramér-Rao lower bounds (CRLBs) for the multi-parameter estimation problem are derived. A data-aided least-squares (LS) estimator for jointly obtaining the channel gains and phase noise parameters is derived. Next, a decision-directed weighted least-squares (WLS) estimator is proposed, where pilots and estimated data symbols are employed to track the time-varying phase noise parameters over a frame. In order to reduce the overhead and delay associated with the estimation process, a new decision-directed extended Kalman filter (EKF) is proposed for tracking the MIMO phase noise throughout a frame. Numerical results show that the proposed LS, WLS, and EKF estimators' performances are close to the CRLB. Finally, simulation results demonstrate that by employing the proposed channel and time-varying phase noise estimators the bit-error rate performance of a MIMO system can be significantly improved.

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KW - Cramér-Rao lower bound (CRLB)

KW - Wiener phase noise

KW - extended Kalman filter (EKF)

KW - multi-input multi-output (MIMO)

KW - weighted least squares (WLS)

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JF - IEEE Transactions on Signal Processing

IS - 9

M1 - 6212402

ER -

Joint estimation of channel and oscillator phase noise in MIMO systems

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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