Comparison of Data-Aided SFO Estimation Algorithms in DDO-OFDM

We investigate the estimation error, convergence speed, and computational complexity of the three commonly used sampling frequency offset (SFO) estimation algorithms based on training sequence (TS), cyclic prefix (CP), and pilot under different signal-to-noise ratios (SNRs) and received optical powers (ROPs) by numerical simulation and offline experiment in a short-reach direct-detection optical OFDM transmission system. The results showed that the pilot-based algorithm's estimation accuracy (< 14 ppm) is relatively low for the initial SFOs in the range of +/- 200 ppm, while the estimation error of both TS-based and CP-based algorithms is stable within 0.6 ppm. Moreover, pilot-based and TS-based algorithms exhibit a faster convergence speed than the CP-based one. And the computational complexity of the SFO estimation algorithms based on CP, TS, and pilot decreases sequentially.