Conference proceeding
Ber analysis of the box relaxation for BPSK signal recovery
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vol.2016-, pp.3776-3780
03/2016
DOI: 10.1109/ICASSP.2016.7472383
Abstract
We study the problem of recovering an n-dimensional BPSK signal from m linear noise-corrupted measurements using the box relaxation method which relaxes the discrete set {±1}n to the convex set [-1,1]n to obtain a convex optimization algorithm followed by hard thresholding. When the noise and measurement matrix have iid standard normal entries, we obtain an exact expression for the bit-wise probability of error Pe in the limit of n and m growing and m/n fixed. At high SNR our result shows that the Pe of box relaxation is within 3dB of the matched filter bound (MFB) for square systems, and that it approaches the (MFB) as m grows large compared to n. Our results also indicate that as m, n → ∞, for any fixed set of size k, the error events of the corresponding k bits in the box relaxation method are independent.
Details
- Title: Subtitle
- Ber analysis of the box relaxation for BPSK signal recovery
- Creators
- Christos Thrampoulidis - California Institute of TechnologyEhsan Abbasi - California Institute of TechnologyWeiyu Xu - University of IowaBabak Hassibi - California Institute of Technology
- Resource Type
- Conference proceeding
- Publication Details
- 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vol.2016-, pp.3776-3780
- Publisher
- IEEE
- DOI
- 10.1109/ICASSP.2016.7472383
- ISSN
- 1520-6149
- eISSN
- 2379-190X
- Language
- English
- Date published
- 03/2016
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197350602771
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