Near Optimum Low Complexity Smoothing Loops for Dynamical Phase Estimation—Application to BPSK Modulated Signals

Jianxiao Yang (1) , Benoit Geller (1)

1 IS - Ingénierie Systèmes

—This correspondence provides and analyzes a low complexity, near optimum, fixed-interval smoothing algorithm that approaches the performance of an optimal smoother for the price of two low complexity sequential estimators, i.e., two phase-locked loops (PLLs). Based on a linear approximation of the problem, a theoretical performance evaluation is given. The theoretical results are compared to some simulation results and to the Bayesian and hybrid Cramér–Rao bounds. They illustrate the good performance of the proposed smoothing PLL (S-PLL) algorithm. Index Terms—Dynamical phase estimation, phase-locked loop (PLL), smoothing algorithm.

Domaines: Réseaux et télécommunications [cs.NI]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Jianxiao Yang, Benoit Geller. Near Optimum Low Complexity Smoothing Loops for Dynamical Phase Estimation—Application to BPSK Modulated Signals. IEEE Transactions on Signal Processing, 2009, pp.3704-3711. ⟨10.1109/TSP.2009.2021452⟩. ⟨hal-01180826⟩