@inproceedings{8d473b313d294586a657e7fde7470146,
title = "Multi-coset sampling and reconstruction of signals: Exploiting sparsity in spectrum monitoring",
abstract = "We present an analytical representation of multi-coset sampling (MCS) and implement the proposed scheme on spectrum data to analyze the effect of MCS that requires less samples. Sampling pattern (SP) selection, which is one of the most significant phases of MCS, is investigated and the effect of the SP on reconstruction matrices and reconstruction process of the signal is analyzed. Different algorithms, which aim to find the optimum SP, are presented and their performances are compared. In order to present the feasibility of the process, MCS is implemented to measurements captured by a spectrum analyzer. The wideband spectrum measurements are obtained over 700-3000 MHz. They are sub-sampled and reconstructed again, so that the RMSE values of the reconstructed signals are evaluated. Effects of the SP search algorithms on the reconstruction process are analyzed for the spectrum monitoring application.",
keywords = "Condition number, Multicoset sampling, Sampling pattern selection, Sparsity, Spectrum monitoring",
author = "Celebi, {Hasan Basri} and Lutfiye Durak-Ata and Hasari Celebi",
year = "2013",
language = "English",
isbn = "9780992862602",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
booktitle = "2013 Proceedings of the 21st European Signal Processing Conference, EUSIPCO 2013",
note = "2013 21st European Signal Processing Conference, EUSIPCO 2013 ; Conference date: 09-09-2013 Through 13-09-2013",
}