noise folding compensation in compressed sensing based matched-filter receiver

Background and objectives: compressed sensing (cs) of analog signals in shift-invariant spaces can be used to reduce the complexity of the matched-filter (mf) receiver, in which we can be approached the standard mf performance with fewer filters. but, with a small number of filters the performance degrades quite rapidly as a function of snr. in fact, the cs matrix aliases all the noise components, therefore the noise increases in the compressed measurements. this effect is referred to as noise folding. in this paper, an approach for compensating the noise folding effect is proposed. methods: an approach for compensating of this effect is to use a sufficient number of filters. in this paper the aim is to reach the better performance with the same number of filter as in the previous work. this, can be approached using a weighting function embedded in the analog signal compressed sensing structure. in fact, using this weighting function we can remedy the effect of cs matrix on the noise variance. results: comparing with the approach based on using the sufficient number of filters to counterbalance the noise increase, experimental results show that with the same numbers of filters, in terms of probability of correct detection, the proposed approach remarkably outperforms the rival’s.conclusion: noise folding formation is the main factor in cs-based matched-filter receiver. the method previously presented to reduce this effect demanded using the sufficient number of filters which comes at a cost. in this paper we propose a new method based on using the weighting function embedded in the analog signal compressed sensing structure to achieve better performance.