DFT Based Method for Accurate I/Q Imbalance Estimation
This paper presents a new all-digital blind algorithm based on three-point Discrete Fourier Transform (DFT) interpolation algorithm for the accurate calibration of in-phase (I) and quadrature (Q) imbalance in the direct-conversion transceivers. The subject of the algorithm can be a wireless local ar...
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| Veröffentlicht in: | IEEE transactions on circuits and systems. II, Express briefs Jg. 71; H. 4; S. 1 |
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| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
IEEE
01.04.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Schlagworte: | |
| ISSN: | 1549-7747, 1558-3791 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | This paper presents a new all-digital blind algorithm based on three-point Discrete Fourier Transform (DFT) interpolation algorithm for the accurate calibration of in-phase (I) and quadrature (Q) imbalance in the direct-conversion transceivers. The subject of the algorithm can be a wireless local area network (WLAN) 802.11a/b/g/j/p/n/ac/ax/be test application. The proposed three-point DFT interpolation algorithm can calculate system frequency of the received signals to achieve the unbiased estimation, and it can be extended to calculate each subcarrier frequency offset of the orthogonal frequency division multiplexing (OFDM) signal. In the signal-to-noise ratio test, the signal-to-noise ratio (SNR) is set to 40 dB, the simulation results show that the image rejection ratio (IRR) of the received signals calibrated by the proposed algorithm can always reach to more than 60 dB under various test environments, and the mean square error (MSE) of the baseband frequency estimation is always below -85 dB. The proposed algorithm can exhibit the better performance in the vast majority of cases compared with some existing algorithms. In addition, the proposed algorithm can maintain good performance in RF conformance testing. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1549-7747 1558-3791 |
| DOI: | 10.1109/TCSII.2023.3336189 |