Wideband Spectrum Sensing with Sub-Nyquist Sampling in Cognitive Radios
Hongjian Sun, Wei-Yu Chiu, Jing Jiang, Arumugam Nallanathan, and H. Vincent Poor
TL;DR
This paper introduces MASS, a sub-Nyquist sampling method for wideband spectrum sensing in cognitive radios, which reduces sampling rates while maintaining spectral recovery capabilities.
Contribution
The paper proposes MASS, a novel multi-rate asynchronous sub-Nyquist sampling technique with derived spectral recovery conditions and success probability analysis.
Findings
MASS achieves lower sampling rates than previous methods.
Spectral recovery conditions for MASS are established.
The probability of successful spectral recovery is quantified.
Abstract
Multi-rate asynchronous sub-Nyquist sampling (MASS) is proposed for wideband spectrum sensing. Corresponding spectral recovery conditions are derived and the probability of successful recovery is given. Compared to previous approaches, MASS offers lower sampling rate, and is an attractive approach for cognitive radio networks.
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