In this paper we analyze the mean squared error (MSE) for one-bit compressed sensing schemes based on measurement matrices that correspond to unit norm tight frames. We show that, as in the unquantized case, sensing with unit norm tight frames improves the MSE in the reconstruction of sparse vectors from one-bit measurements using l1 and thresholding algorithms. From our analytical and experimental results we conclude that when implementing one-bit compressed sensing schemes with fixed measurement matrices unit norm tight frames are the measurements of choice

%B IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) %8 2016 %G eng %0 Conference Paper %B IEEE Global Telecommunications Conf. (GLOBECOM), %D 2015 %T Adaptive one-bit compressive sensing with application to low-precision receivers at mmWave %A C. Rusu %A R. Méndez-Rial %A Nuria González-Prelcic %A R. W. Heath, Jr %K compass %K mmWave %B IEEE Global Telecommunications Conf. (GLOBECOM), %8 December, 2015 %G eng %0 Conference Paper %B Asilomar Conf. on Signals, Systems, and Computers %D 2015 %T Low Resolution Adaptive Compressed Sensing for mmWave MIMO receivers %A C. Rusu %A Nuria González-Prelcic %A R.W. Heath Jr. %K compass %K mmWave %B Asilomar Conf. on Signals, Systems, and Computers %8 November, 2015 %G eng