Sparsity-Driven Multiple Access Ultra-Wideband Signal Detection

Ultra-Wideband (UWB) transmission is a promising technology for high speed wireless networks such as wireless personal area networks (WPANs). The detection of UWB signals is a key issue for system performance and capacity. In this paper, we propose a novel signal detection technique for multiple access UWB systems. Our approach is based on an overcomplete dictionary signal representation as well as the concept of successive interference cancellation for multi-user detection. We introduce the algorithm for multiple access UWB signal detection, and present guidelines to generate overcomplete dictionaries for the detection of signals in noise. The proposed detection algorithm for multiple access UWB systems can eliminate noise as well as multi-user interference (MUI). Signal detection is achieved by solving an l₁ norm minimization problem, which can be calculated using low complexity linear programming algorithms