dc.contributor.author Ben Atitallah, Ismail dc.contributor.author Thrampoulidis, Christos dc.contributor.author Kammoun, Abla dc.contributor.author Al-Naffouri, Tareq Y. dc.contributor.author Hassibi, Babak dc.contributor.author Alouini, Mohamed-Slim dc.date.accessioned 2017-10-03T12:49:30Z dc.date.available 2017-10-03T12:49:30Z dc.date.issued 2017-06-20 dc.identifier.citation Ben Atitallah I, Thrampoulidis C, Kammoun A, Al-Naffouri TY, Hassibi B, et al. (2017) BER analysis of regularized least squares for BPSK recovery. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Available: http://dx.doi.org/10.1109/ICASSP.2017.7952960. dc.identifier.doi 10.1109/ICASSP.2017.7952960 dc.identifier.uri http://hdl.handle.net/10754/625622 dc.description.abstract This paper investigates the problem of recovering an n-dimensional BPSK signal x0 {’1, 1}$^{n}$ from m-dimensional measurement vector y = Ax+z, where A and z are assumed to be Gaussian with iid entries. We consider two variants of decoders based on the regularized least squares followed by hard-thresholding: the case where the convex relaxation is from {’1, 1}$^{n}$ to „ $^{n}$ and the box constrained case where the relaxation is to [’1, 1]$^{n}$. For both cases, we derive an exact expression of the bit error probability when n and m grow simultaneously large at a fixed ratio. For the box constrained case, we show that there exists a critical value of the SNR, above which the optimal regularizer is zero. On the other side, the regularization can further improve the performance of the box relaxation at low to moderate SNR regimes. We also prove that the optimal regularizer in the bit error rate sense for the unboxed case is nothing but the MMSE detector. dc.description.sponsorship This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/2221-01. dc.publisher Institute of Electrical and Electronics Engineers (IEEE) dc.relation.url http://ieeexplore.ieee.org/document/7952960/ dc.subject Binary phase shift keying dc.subject Bit error rate dc.subject Closed-form solutions dc.subject Decoding dc.subject Detectors dc.subject Error probability dc.subject Signal to noise ratio dc.title BER analysis of regularized least squares for BPSK recovery dc.type Conference Paper dc.contributor.department Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division dc.contributor.department Electrical Engineering Program dc.identifier.journal 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) dc.conference.date 2017-03-05 to 2017-03-09 dc.conference.name 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 dc.conference.location New Orleans, LA, USA dc.contributor.institution Department of Electrical Engeeniring, Caltech, Pasadena, USA kaust.person Ben Atitallah, Ismail kaust.person Kammoun, Abla kaust.person Al-Naffouri, Tareq Y. kaust.person Alouini, Mohamed-Slim kaust.grant.number URF/1/2221-01 dc.date.published-online 2017-06-20 dc.date.published-print 2017-03
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