Low-complexity Data-aided Timing Acquisition for Time Hopping Uwb Impulse Radios

Timing acquisition is critical to enabling the potential of ultra-wideband impulse radios in high-speed, short-range indoor wireless networking. To this end, optimum data-aided timing offset estimators are derived in this paper based on the maximum likelihood (ML) criterion. A generalized likelihood ratio test (GLRT) is employed to detect an ultra-wideband waveform propagating through dense multipath, as well as to estimate the associated timing and channel parameters in closed form. In a data-aided mode, the GLRT boils down to amplitude estimation, where the impact of time hopping (TH) is captured by channel-dependent amplitudes of frame-rate correlator output samples and estimated via conditional ML formulation. The desired timing information can then be recovered from the amplitude fluctuation pattern in the presence of TH. The proposed algorithms only employ digital samples collected at a low frame rate, thus reducing considerably the implementation complexity and acquisition time.