One-bit compressive sensing vs. multi-bit compressive sensing for cognitive radio networks

Compressive sensing has been proposed as an alternative solution for signal acquisition to directly acquire compressible signals at a rate lower than the Nyquist rate. Compressive sensing techniques can be classified into two categories: one-bit compressive sensing and multi-bit compressive sensing. One-bit compressive sensing performs by acquiring only the sign of each measurement while multi-bit compressive sensing performs by acquiring multiple bits. In this paper, we analyze the performance of each category. We compare their efficiencies using metrics that cover the most aspects of the compressive sensing performance in cognitive radio networks. Simulation results show that one-bit compressive sensing can outperform the multi-bit compressive sensing in terms of speed, robustness to noise, complexity, and reconstruction success rate.