  In this paper we consider the generalized approximate message passing (GAMP)
algorithm for recovering a sparse signal from modulo samples of randomized
projections of the unknown signal. The modulo samples are obtained by a
self-reset (SR) analog to digital converter (ADC). Additionally, in contrast to
previous work on SR ADC, we consider a scenario where the compressed sensing
(CS) measurements (i.e., randomized projections) are sent through a
communication channel, namely an additive white Gaussian noise (AWGN) channel
before being quantized by a SR ADC. To show the effectiveness of the proposed
approach, we conduct Monte-Carlo (MC) simulations for both noiseless and noisy
case. The results show strong ability of the proposed algorithm to fight the
nonlinearity of the SR ADC, as well as the possible additional distortion
introduced by the AWGN channel.
