Compressive sensing-based signal compression and recovery in UWB wireless communication system

摘要

In this paper, we propose a new compressive sensing-based compression and recovery ultra-wideband (UWB) communication system. Compared with the conventional UWB system, we can jointly estimate the channel and compress the data, which can also simplify the design of hardware. No information about the transmitted signal is required in advance as long as the channel follows autoregressive process. As an application example, real-world UWB signal is collected and processed to evaluate the performance of our proposed system. The compression procedure is so simple that we just multiply random Gaussian or Bernoulli matrix with the original data to capture all the information we want. Simulation results show that the data could be perfectly recovered if the compression ratio does not exceed 2.5:1 when Bernoulli matrix is chosen as the sensing matrix.