Title
Impact of channel models on compressed sensing recovery algorithms-based ultra-wideband channel estimation
Abstract
Multipath arrivals in an ultra-wideband (UWB) channel have long time intervals between clusters and rays where the signal takes on zero or negligible values. It is precisely this signal sparsity of the impulse response of the UWB channel that is suitable for the application of compressed sensing (CS) theory. However, these multipath arrivals mainly depend on the channel models that generate different sparse levels (low-sparse or high-sparse) of channels according to which, the authors have analysed and chosen the best recovery algorithms which are suitable for the sparse level for each type of channel model. Criteria for evaluating the algorithms are based on computational complexity, ability to reduce the sampling rate and processing time. Besides, the results of this work are an open topic for further research aimed at creating an optimal algorithm specially for application of CS-based UWB systems.
Year
DOI
Venue
2013
10.1049/iet-com.2013.0240
IET Communications
Keywords
Field
DocType
sampling rate,uwb channel,signal sparsity,cs-based uwb systems,long time intervals,ultra wideband communication,compressed sensing recovery algorithms-based ultra-wideband channel estimation,computational complexity,compressed sensing theory,compressed sensing,transient response,channel models,impulse response,processing time,channel estimation
Multipath propagation,Impulse response,Channel models,Computer science,Sampling (signal processing),Communication channel,Algorithm,Ultra-wideband,Compressed sensing,Computational complexity theory
Journal
Volume
Issue
ISSN
7
13
1751-8628
Citations 
PageRank 
References 
3
0.57
3
Authors
3
Name
Order
Citations
PageRank
Nguyen Thanh Son1357.03
Shuxu Guo2196.12
Haipeng Chen3397.64