Low Sampling Rate Time Acquisition Schemes and Channel Estimation Algorithms of Ultra-Wideband Signals

Abstract

Ultra-wideband (UWB) communication is a viable technology to provide high data rates over broadband wireless channels for applications, including wireless multimedia, wireless Internet access, and future-generation mobile communication systems (Karaoguz, 2001; Stoica et al., 2005). Two of the most critical challenges in the implementation of UWB systems are the timing acquisition and channel estimation. The difficulty in them arises from UWB signals being the ultra short low-duty-cycle pulses operating at very low power density. The Rake receiver (Turin, 1980) as a prevalent receiver structure for UWB systems utilizes the high diversity in order to effectively capture signal energy spread overmultiple paths and boost the received signal-to-noise ratio (SNR). However, to perform maximal ratio combining (MRC), the Rake receiver needs the timing information of the received signal and the knowledge of the channel parameters, namely, gains and tap delays. Timing errors as small as fractions of a nanosecond could seriously degrade the system performance (Lovelace & Townsend, 2002; Tian & Giannakis, 2005). Thus, accurate timing acquisition and channel estimation is very essentially for UWB systems. Many research efforts have been devoted to the timing acquisition and channel estimation of UWB signals. However, most reported methods suffer from the restrictive assumptions, such as, demanding a high sampling rates, a set of high precision time-delay systems or invoking a line search, which severally limits their usages. In this chapter, we are focusing on the low sampling rate time acquisition schemes and channel estimation algorithms of UWB signals. First, we develop a novel optimum data-aided (DA) timing offset estimator that utilizes only symbol-rate samples to achieve the channel delay spread scale timing acquisition. For this purpose, we exploit the statistical properties of the power delay profile of the received signals to design a set of the templates to ensure the effective multipath energy capture at any time. Second, we propose a novel optimum data-aided channel estimation scheme that only relies on frame-level sampling rate data to derive channel parameter estimates from the received waveform. The simulations are provided to demonstrate the effectiveness of the proposed approach. Low Sampling Rate Time Acquisition Schemes and Channel Estimation Algorithms of Ultra-Wideband Signals