On the Optimality of Data-Aided Coarse Timing With Dirty Templates

作     者：Zhang, Wenshu Yang, Liuqing Cheng, Xiang Zang, Wei 

作者机构：Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Peking Univ Sch Elect Engn & Comp Sci Beijing 100871 Peoples R China MathWorks Inc Natick MA 01760 USA 

出 版 物：《IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY》 (IEEE Trans. Veh. Technol.)

年 卷 期：2014年第63卷第4期

页      面：1759-1769页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0823[工学-交通运输工程] 

基　　金：National Natural Science Foundation [61101079, 61172105, 61322107] Science Foundation for the Youth Scholar of the Ministry of Education of China State Key Laboratory of Management and Control for Complex Systems of the Chinese Academy of Sciences 

主　　题：Maximum-likelihood (ML) estimation timing synchronization ultrawideband (UWB) systems 

摘      要：Rapid and accurate timing synchronization is a critical task in ultrawideband (UWB) systems. Yang and Giannakis introduced a promising algorithm, i.e., data-aided timing with dirty templates (TDT), which is known for low complexity and relaxed operation conditions in the presence of unknown time hopping and multipath channels. In this paper, we will explore the optimality of TDT. We develop a maximum-likelihood (ML) timing algorithm and obtain its optimum training sequence. It is shown that the optimum training sequence of the ML timing estimator coincides with that of the TDT algorithm. In addition, we prove that the ML algorithm can be simplified using this training sequence and that the simplified ML (SML) is equivalent to TDT.