Application of compressed sensing in cognitive radio

Abstract

In the last few years, compressed sensing (CS) has been well used in the area of signal processing and image compression. Recently, CS has been earning a great interest in the area of wireless communication systems. CS exploits the sparsity of the signal processed for digital acquisition to reduce the number of measurement, which leads to reductions in the size, power consumption, processing time, and processing cost. This paper presents application of CS in cognitive radio (CR) networks for spectrum sensing and channel estimation. The effectiveness of the proposed CS-based scheme is demonstrated through comparisons with the existing conventional spectrum sensing and channel estimation methods.