An Efficient Blind Carrier Frequency Offset Estimation Algorithm for QAM

This paper presents a method for blind carrier frequency offset (CFO) estimation for quadrature amplitude modulation (QAM). Our proposed algorithm has three major steps, including two-stage full modulation removal, symbol aggregation, and iterative parabolic interpolation. In the first step, a preliminary CFO estimate will be evaluated using the QPSK sub-constellations. The modulation values of the remaining constellation points are partially removed based on the preliminary CFO estimate, and the residual modulation values are quantized to achieve the full modulation removal. In the second step, modulation-removed symbols are paired and weighted based on their reliability levels. This symbol aggregation step improves the estimation accuracy and reduces the FFT size of the following FFT-based CFO estimation. A trade-off between performance and complexity can be achieved by adjusting the aggregation length. In the final step, an iterative parabolic interpolation technique is introduced to mitigate the estimation bias. Performance evaluation shows that the proposed method provides better mean square error (MSE) performance and comparable complexity compared to the existing CFO methods for QAM.

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Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174686
Primary Topic
Blind Source Separation Techniques
Type
article
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An Efficient Blind Carrier Frequency Offset Estimation Algorithm for QAM

Yu‐Ting Kuo, Huang–Chang Lee, Yeong-Luh Ueng, Hongyu You
Blind Source Separation Techniques
article

An Efficient Blind Carrier Frequency Offset Estimation Algorithm for QAM

Yu‐Ting Kuo, Huang–Chang Lee, Yeong-Luh Ueng, Hongyu You
article en

Abstract

This paper presents a method for blind carrier frequency offset (CFO) estimation for quadrature amplitude modulation (QAM). Our proposed algorithm has three major steps, including two-stage full modulation removal, symbol aggregation, and iterative parabolic interpolation. In the first step, a preliminary CFO estimate will be evaluated using the QPSK sub-constellations. The modulation values of the remaining constellation points are partially removed based on the preliminary CFO estimate, and the residual modulation values are quantized to achieve the full modulation removal. In the second step, modulation-removed symbols are paired and weighted based on their reliability levels. This symbol aggregation step improves the estimation accuracy and reduces the FFT size of the following FFT-based CFO estimation. A trade-off between performance and complexity can be achieved by adjusting the aggregation length. In the final step, an iterative parabolic interpolation technique is introduced to mitigate the estimation bias. Performance evaluation shows that the proposed method provides better mean square error (MSE) performance and comparable complexity compared to the existing CFO methods for QAM.

National Taiwan Ocean University (TW), National Tsing Hua University (TW)
Openalex Percentile: Top 67%
Blind Source Separation Techniques
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An Efficient Blind Carrier Frequency Offset Estimation Algorithm for QAM — Yu‐Ting Kuo, Huang–Chang Lee, et al. · (2025) | TGRS Research Map | TGRS