Abstract
The overall system efficiency of impulse radio communications relies critically on judicious allocation of transmission resources, a portion of which should be used to ensure successful timing acquisition. In data-aided mode, optimum tuning offset estimation depends not only on the mechanism used for energy capture and the acquisition algorithm employed to recover timing information, but also on the training sequence (TS) pattern from which the timing information is to be extracted. Furthermore, the transmission resources used for timing have to be balanced with that for conveying information messages in order to strike desirable tradeoffs between timing accuracy and information rate. In Part I of this paper, data-aided timing offset estimation is derived based on the maximum likelihood (ML) criterion, where only symbol-rate samples are needed for low-complexity receiver processing. To minimize the mean-square timing errors of these ML synchronizers while at the same time maximizing the average system capacity, TS design and transmit power allocation are investigated in this paper. The optimum training pattern and the number, placement, and power distribution between training and information-bearing symbols are formulated as a resource allocation optimization problem whose solution optimizes system-level performance with the minimum amount of resources consumed.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2994-3004 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Wireless Communications |
| Volume | 4 |
| Issue number | 6 |
| DOIs | |
| State | Published - Nov 2005 |
Bibliographical note
Funding Information:Manuscript received February 12, 2004; revised August 15, 2004; accepted October 11, 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 and Grant ECS-0427430. The work of G. B. Giannakis was supported by the Army Research Laboratory/Collaborative Technology Alliance (ARL/CTA) under Grant DAAD19-01-2-011 and by the National Science Foundation-Information Technology Research (NSF-ITR) under Grant EIA-0324864. This paper was presented in part at the International Conference on Communications (ICC’2004), Paris, France, June 2004.
Keywords
- Data-aided estimation
- Timing acquisition
- Training sequence (TS) design
- Transmission resource allocation
- Ultrawide-band (UWB) communications
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