Compressed sampling based on circulant matrix for analog signals

In order to implement the high-speed data transmission in wireless communication system, the signal bandwidth becomes wider. However this results in high Nyquist sampling rate which will beyond the capacity of the hardware device. The analog-to-information conversion (AIC) based on compressed sensing (CS) is proposed to sample signals at a sub-Nyquist rate. The circulant matrix (CM) instead of the random Bernoulli matrix is used as the measurement matrix in this paper. Compared with the structure based on random Bernoulli matrix, this CM based architecture, in a certain extent, can reduce system complexity. Simulations which show the efficiency of the proposed approach are also presented.