Abstract
Modulation classification is an intermediate step between signal detection and demodulation, and plays a key role in various civilian and military applications. In this correspondence, higher-order cyclic cumulants (CCs) are explored to discriminate linear digital modulations in flat fading channels. Single- and multi-antenna CC-based classifiers are investigated. These benefit from the robustness of the CC-based features to unknown phase and timing offset. Furthermore, the latter provides significant performance improvement due to spatial diversity used to combat the fading effect. Classifier performances are investigated under a variety of channel conditions. In addition, analytical closed-form expressions for the cyclic cumulant polyspectra of linearly digitally modulated signals affected by fading, carrier frequency and timing offsets, and additive Gaussian noise are derived, along with a condition for the oversampling factor to avoid aliasing in the cycle and spectral frequency domains.
Original language | English (US) |
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Pages (from-to) | 699-717 |
Number of pages | 19 |
Journal | Wireless Personal Communications |
Volume | 54 |
Issue number | 4 |
DOIs | |
State | Published - Sep 2010 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
Keywords
- Antenna arrays
- Automatic modulation classification
- Cycle aliasing
- Higher-order cyclic statistics
- Probability of correct classification
- Selection combining