Data-aided timing estimation in UWB communication systems using dirty templates

Timing acquisition represents a major challenge in carrying out highly efficient ultra-wideband (UWB) communications. The timing with dirty template (TDT) approach is a promising candidate, which is low-complexity high-performance timing acquisition. In this paper, we describe the dirty template (DT) technique, in order to develop and test timing algorithms in Data Aided (DA) mode. In addition, we derive the Cramer-Rao low bound, which is used as fundamental performance limit for any timing estimator. Next, the TDT acquisition estimator is achieved by using Maximum Likelihood (ML) concept. Simulation results confirm that the timing estimation performance is improved with either the signal-to-noise ratio (SNR) or the training sequence number increases.

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