Soft Information Improvement for PN Sequence Iterative Acquisition

Abstract

Iterative message passing algorithms (iMPAs) which are generalized from the well-known turbo principle can reach a rapid pseudo-noise (PN) sequence acquisition at low computational complexity. However, its performance will degrade at low signal-to-noise ratio (SNR). In this paper, a soft information improvement using multiple samples in one chip is proposed. Meanwhile, to mitigate the timing error which will affect the information improvement, a Maximum-Likelihood (ML) estimation without significant increase on the complexity is introduced. Simulation results show that proposed method can realize rapid PN code acquisition at lower SNR than existing method.