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Near MAP Dynamical Delay Estimator and Bayesian CRB for Coded QAM Signals

Abstract : This paper presents an off-line algorithm for dy-namical time delay recovery for which the whole observation block is used. The time offset varies over the observation interval following a random walk model. The proposed synchronizer applies to data-aided (DA), non-data-aided (NDA) and code-aided (CA) modes. Theoretical performance of the off-line technique is derived and compared to simulation results. The Bayesian Cramer-Rao Bound (BCRB) is also evaluated for DA, NDA and CA modes and for both the off-line and on-line scenarios. Simulation results show the improvement brought by the off-line and the CA schemes. The presented algorithm outperforms the conventional on-line estimator, which only takes into account the current and previous observations, and its MSE approaches the BCRB.
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Submitted on : Monday, October 30, 2017 - 3:13:51 PM
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Long-term archiving on: : Wednesday, January 31, 2018 - 1:02:52 PM


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Imen Nasr, Leïla Najjar Atallah, Sofiane Cherif, Benoit Geller. Near MAP Dynamical Delay Estimator and Bayesian CRB for Coded QAM Signals. IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers, 2018. ⟨hal-01626247⟩



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