Paper Info
Title
The Importance of Being Earnest: Performance of Modulation Classification for Real RF Signals
Abstract
Digital modulation classification (DMC) can be highly valuable for equipping radios with increased spectrum awareness in complex emerging wireless networks. However, as the existing literature is overwhelmingly based on theoretical or simulation results, it is unclear how well DMC performs in practice. In this paper we study the performance of DMC in real-world wireless networks, using an extensive RF signal dataset of 250,000 over-the-air transmissions with heterogeneous transceiver hardware and co-channel interference. Our results show that DMC can achieve a high classification accuracy even under the challenging real-world conditions of modulated co-channel interference and low-grade hardware. However, this only holds if the training dataset fully captures the variety of interference and hardware types in the real radio environment; otherwise, the DMC performance deteriorates significantly. Our work has two important engineering implications. First, it shows that it is not straightforward to exchange learned classifier models among dissimilar radio environments and devices in practice. Second, our analysis suggests that the key missing link for real-world deployment of DMC is designing signal features that generalize well to diverse wireless network scenarios. We are making our RF signal dataset publicly available as a step towards a unified framework for realistic DMC evaluation.
Year
DOI
Venue
2018
10.1109/DySPAN.2018.8610499
2018 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)
Keywords
DocType
Volume
Signal classification,digital modulation classification,spectrum awareness,support vector machine
Conference
abs/1809.06176
ISSN
ISBN
Citations 
2334-3125
978-1-5386-5192-6
1
PageRank 
References 
Authors
0.37
9
3
Name
Order
Citations
PageRank
Colin de Vrieze110.37
Ljiljana Simic210917.17
Petri Mähönen31610150.99