Ultra-Wideband Compressed Sensing: Channel Estimation

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

“…Since UWB channels exhibit clusters (Cramer et al, 2002), a cluster-based channel estimation method is proposed in (Carbonelli & Mitra, 2007). Different methods such as subspace approach (Xu & Liu, 2003), first-order cyclostationary-based method (Wang & Yang, 2004) and compressed sensing based method (Paredes et al, 2007;Shi et al, 2010) proposed for UWB channel estimation are too complex to be implemented in actual systems. In this section, we develop 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.…”

UWB pulse detection and TOA estimation using GLRT

“…In order to overcome this disadvantage, researchers resort to sub-Nyquist sampling techniques for ranging using sub-nanosecond pulse signals. In [16,17], compressed sampling techniques are applied to realize sub-Nyquist sampling at the expense of a more complex receiver structure. Fontana and Gunderson [18] gives a novel design to obtain TOA measurements directly without sampling of the received signal, where a receiver is used based on a daisy-chain structured tunnel diode detector to detect successive peaks of the measured channel impulse response.…”

Compressed Sensing: Ultra-Wideband Channel Estimation Based on FIR Filtering Matrix

“…It is proved that conventional channel estimation methods provide higher errors because they ignore the prior knowledge of the sparseness (Wan et al, 2010). The sparse channel estimation problem is faced in (Paredes et al, 2007) under a time domain sparse model point of view. In (Paredes et al, 2007) a suitable dictionary formed by delayed versions of the UWB transmitted pulse is defined in order to better match the UWB signal.…”

“…The sparse channel estimation problem is faced in (Paredes et al, 2007) under a time domain sparse model point of view. In (Paredes et al, 2007) a suitable dictionary formed by delayed versions of the UWB transmitted pulse is defined in order to better match the UWB signal. However, the spike basis achieves maximal incoherence with the Fourier basis (Candès & Wakin, 2008) and is for that reason that seems more convenient to work with frequency domain.…”

“…As the IR-UWB signals have resolvable multipath with a sparse structure at the receiver, the application of CS theory to UWB channel estimation has also found wide interest in the UWB community. For the CS based UWB channel estimation, the main goal has been to estimate the sparse channel with reduced number of observations (Paredes et al, 2007;Liu & Lu, 2009;Naini et al, 2009).That is equivalent to reducing the sampling rate at the receiver. In (Paredes et al, 2007), a channel detection method based on the Matching Pursuit algorithm is proposed, where the path delays and gains are calculated iteratively.…”