Overcomplete dictionary based ultra-wideband signal detection

Ultra-wideband (UWB) transmission is a promising technology for future high speed wireless networks. In this paper, we propose a novel signal detection approach with noise suppression for UWB systems. This approach is based on an overcomplete dictionary signal representation and a sparsity-driven optimization algorithm. We introduce general approaches for UWB signal detection, and present guidelines to generate overcomplete dictionaries for signals in noise. UWB signal detection is achieved by solving an l₁ norm minimization problem, which can be solved using low complexity linear programming algorithms. Examples are given to demonstrate the performance of the proposed approach