Bayesian and hybrid Cramer-Rao bounds for QAM dynamical phase estimation
Provides computationally efficient theoretical bounds for phase estimation in QAM synchronization, but the contribution is incremental as it extends existing CRB theory to a specific modulation format.
The paper derives analytical expressions for Bayesian and hybrid Cramer-Rao bounds for dynamical phase estimation of QAM signals, avoiding matrix inversion to reduce computational complexity. Simulations show the bounds' behavior with SNR.
-In this paper, we study Bayesian and hybrid Cramer-Rao bounds for the dynamical phase estimation of QAM modulated signals. We present the analytical expressions for the various CRBs. This avoids the calculation of any matrix inversion and thus greatly reduces the computation complexity. Through simulations, we also illustrate the behaviors of the BCRB and of the HCRB with the signal-to-noise ratio. Index Terms-Bayesian Cramer-Rao Bound (BCRB), Hybrid Cramer-Rao Bound (HCRB), Synchronization Performance