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Spectral analysis based blind frequency offset estimation for digital subcarrier multiplexing systems with adjustable
Optics Express
|November 14, 2024
Summary
A novel blind frequency offset estimation (FOE) method accurately estimates frequency offsets in digital subcarrier multiplexing (DSM) signals. This approach offers improved accuracy and computational efficiency for various modulation schemes and spectral shaping factors.
Area of Science:
- Signal Processing
- Telecommunications Engineering
- Digital Communications
Background:
- Digital Subcarrier Multiplexing (DSM) systems are crucial for high-capacity data transmission.
- Accurate frequency offset estimation (FOE) is essential for maintaining signal integrity in DSM systems.
- Existing FOE methods may lack flexibility or efficiency across diverse modulation schemes and spectral shaping.
Purpose of the Study:
- To develop a blind frequency offset estimation (FOE) method for digital subcarrier multiplexing (DSM) signals.
- To enhance accuracy and computational efficiency in FOE for DSM systems.
- To ensure the proposed method's adaptability to various modulation schemes and spectral shaping parameters.
Main Methods:
- Utilizing spectral information inherent in DSM signals.
- Analyzing the correlation between frequency offset (FO) and the summed power of the signal spectrum.
- Implementing a method flexible to the roll-off factor of root raised cosine (RRC) spectral shaping.
Main Results:
- Achieved high accuracy in FOE with errors less than 30 MHz for an FFT size of 2048.
- Demonstrated effectiveness across various modulation schemes and roll-off factors.
- Showcased reduced computational complexity compared to existing FOE techniques.
- Experimentally verified performance using 48Gbaud 16QAM DSM signals in a coherent detection system.
Conclusions:
- The proposed blind FOE method provides an accurate, efficient, and flexible solution for DSM signals.
- This technique is robust to different modulation schemes and spectral shaping parameters.
- Offers a significant advantage in computational complexity for practical DSM system implementation.
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