Abstract
Conventional fast Fourier transform based frequency offset estimation (FFT-FOE) algorithm is suitable for QPSK and 8/16/64QAM signals. However, due to the non-rectangular distribution of constellation points, the conventional FFT-FOE is not suitable for 32-QAM signal. In this paper, we report a factor \gamma which can indicate whether the FFT-FOE algorithm can be used for frequency offset estimation for different modulation formats. The FFT-FOE algorithm is hard to apply for frequency offset estimation if the value of \gamma is low. Fortunately, the value of \gamma can be increased by digital amplification and phase rotation. Based on the digital amplification and phase rotation, a modified FFT-FOE algorithm is proposed and can realize the frequency offset estimation of 32-QAM signal with only 512 symbols. The bit error ratio (BER) of a 28 Gbaud 32-QAM signal is lower than the soft-decision forward-error correction (SD-FEC) limit with the optical signal-to-noise ratio (OSNR) of 22 dB. The proposed method has better robustness to phase noise. If BER at SD-FEC limit is considered for 28Gbaud 32-QAM signal, the required OSNR is relaxed by 2 dB when the laser linewidth is greater than 5 MHz. This will make sense when the wide-linewidth laser is used in short reach optical communication system. The experimental results from 10 Gbaud 32-QAM system with 300 km fiber transmission indicate that the proposed method can be applied when OSNR is greater than 14 dB. The results demonstrate that the proposed frequency offset estimation scheme is also suitable for QPSK and 8/16/64QAM signals. Thus, the proposed algorithm can perform blind frequency offset estimation for a coherent transceiver.
| Original language | English |
|---|---|
| Article number | 9050437 |
| Pages (from-to) | 1-12 |
| Number of pages | 12 |
| Journal | IEEE Photonics Journal |
| Volume | 12 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Apr 2020 |
Keywords
- Frequency offset estimation
- amplification and phase rotation
- fast Fourier transform
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