Realizing the great potential of impulse radio communications depends critically on the success of timing acquisition. To this end, optimum data-aided (DA) timing offset estimators are derived in this paper based on the maximum likelihood (ML) criterion. Specifically, generalized likelihood ratio tests (GLRTs) are employed to detect an ultrawideband (UWB) waveform propagating through dense multipart) and to estimate the associated timing and channel parameters in closed form. Capitalizing on the pulse repetition pattern, the GLRT boils down to an amplitude estimation problem, based on which closed-form timing acquisition estimates can be obtained without invoking any line search. The proposed algorithms only employ digital samples collected at a low symbol rate, thus reducing considerably the implementation complexity and acquisition time. Analytical acquisition performance bounds and corroborating simulations are also provided.
Bibliographical noteFunding Information:
Manuscript received January 19, 2004; revised April 25, 2004; accepted August 31, 2004. The editor coordinating the review of this paper and approving it for publication is G. M. Vitetta. The work of Z. Tian was supported by the National Science Foundation (NSF) under Grant CCR-0238174. The work of G. B. Giannakis was supported by the ARL/CTA under Grant DAAD19-01-2-011 and by NSF-ITR under Grant EIA-0324864. This paper was presented in part at the 2003 IEEE Conference on Ultra Wideband Systems and Technologies (UWBST’2003), Reston, VA, November 2003.
- Data-aided acquisition
- Generalized likelihood ratio test
- Timing recovery
- Ultrawideband communications