Blind symbol rate estimation based on BPF bank

Abstract

Conventional real-time symbol rate estimation algorithm is based on the Fourier transform of the signal complex envelope. While this method is economic in resource consumption, its performance deteriorates at low signal-to-noise ratio (SNR), especially for the short burst signal applications. In this paper, we propose a novel method of using bandpass filter (BPF) bank to improve short burst signal's symbol rate estimation performance at low SNR or ratio of symbol energy to noise power spectral density (EsNo), equivalently. Simulation results show that our proposed algorithm can efficiently estimate symbol rate by using 200 symbols at 4 dB EsNo.