Adaptive analog-to-information converter with Limited Random Sequence modulation

Compressive sensing enables quite lower sampling rate compared with Nyquist sampling. As long as the signal is sparsity in some basis, the random sampling with CS can be employed. In order to make CS be applied in the practice, the Analog to Information Converter (AIC) should be involved. Based on the Limited Random Sequence (LRS) modulation, the AIC with LRS can be designed with high performance according to the fixed sparsity. However, if the sparsity of the signal varies with time, the original AIC with LRS is not efficient. In this paper, the adaptive AIC which adapts its scheme of LRS according to the variation of the sparsity is proposed. Due to the adaption of the AIC with the scheme of LRS, the sampling rate and measurement complexity are further reduced. The simulation results confirm the performance of the proposed adaptive AIC scheme.