Particle Filter for Joint Blind Carrier Frequency Offset Estimation and Data Detection

Abstract

This paper proposes a new blind algorithm for joint carrier offset estimation and data detection, which is based on particle filtering and recursively estimates the joint posterior probability density function of the unknown transmitted data and the unknown carrier offset. We develop new guidelines for resampling of the particles to take into account carrier offset estimation ambiguity at the edges of the range, and for fine tuning estimates to achieve fast, accurate convergence. The Mean Square Error (MSE) and Bit Error Rate (BER) performance of the proposed algorithm is studied through computer simulations. The results show that the proposed algorithm achieves fast convergence for the full acquisition range for normalized carrier frequency offsets.