Multipath arrivals in an Ultra-WideBand (UWB) channel have a long time intervals between clusters and rays where the signal takes on zero or negligible values. It is precisely the signal sparsity of the impulse response of the UWB channel that is exploited in this work aiming at UWB channel estimation based on Compressed Sensing (CS). However, these multipath arrivals mainly depend on the channel environments that generate different sparse levels (low-sparse or high-sparse) of the UWB channels. According to this basis, we have analyzed the two most basic recovery algorithms, one based on linear programming Basis Pursuit (BP), another using greedy method Orthogonal Matching Pursuit (OMP), and chosen the best recovery algorithm which are suitable to the sparse level for each type of channel environment. Besides, the results of this work is an open topic for further research aimed at creating a optimal algorithm specially for application of CS based UWB systems.
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