Symbol Synchronization of Single-Carrier Signal with Ultra-Low Oversampling Rate Based on Polyphase Filter

An efficient single-carrier symbol synchronization method is proposed in this paper,which can work under a very low oversampling rate.This method is based on the frequency aliasing squared timing recovery assisted by pilot symbols and time domain filter.With frequency aliasing squared timing recovery with pilots,it is accessible to estimate timing error under oversampling rate less than 2.The time domain filter simultaneously performs matched-filtering and arbitrary interpolation.Because of pilot assisting,timing error estimation can be free from alias and self noise,so our method has good performance.Compared with traditional time-domain methods requiring oversampling rate above 2,this method can be adapted to any rational oversampling rate including less than 2.Moreover,compared with symbol synchronization in frequency domain which can operate under low oversampling rate,our method saves the complicated operation of conversion between time domain and frequency domain.By low oversampling rate and resource saving filter,this method is suitable for ultra-high-speed communication systems under resource-restricted hardware.The paper carries on the simulation and realization under 64QAM system.The simulation result shows that the loss is very low(less than 0.5 dB),and the real-time implementation on field programmable gate array(FPGA)also works fine.

Deep learning-based symbol detection algorithm in IMDD-OOFDM system

In the current research on intensity-modulation and direct-detection optical orthogonal frequency division multiplexing(IMDD-OOFDM) system, effective channel compensation is a key factor to improve system performance. In order to improve the efficiency of channel compensation, a deep learning-based symbol detection algorithm is proposed in this paper for IMDD-OOFDM system. Firstly, a high-speed data streams symbol synchronization algorithm based on a training sequence is used to ensure accurate symbol synchronization. Then the traditional channel estimation and channel compensation are replaced by an echo state network(ESN) to restore the transmitted signal. Finally, we collect the data from the system experiment and calculate the signal-to-noise ratio(SNR). The analysis of the SNR optimized by the ESN proves that the ESN-based symbol detection algorithm is effective in compensating nonlinear distortion.