Advanced spectrum sensing with parallel processing based on software-defined radio

被引:0
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作者
Wei Liu
Daan Pareit
Eli De Poorter
Ingrid Moerman
机构
[1] Ghent University - iMinds,Internet Based Communication Networks and Services (IBCN), Department of Information Technology
关键词
Fast Fourier Transform; Cognitive Radio; Spectrum Analyzer; Sweep Time; Clear Channel Assessment;
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中图分类号
学科分类号
摘要
Due to interference between co-located wireless networks, obtaining accurate channel assessment becomes increasingly important for wireless network configuration. This information is used, among others, for cognitive radio solutions and for intelligent channel selection in wireless networks. Solutions such as spectrum analyzers are capable of scanning a wide spectrum range, but are not dedicated for channel occupation assessment because they are extremely costly and not able to perform continuous recording for a time period longer than a few seconds. On the other hand, low-cost solutions lack the flexibility and required performance in terms of configuration and sensing efficiency. To remedy the situation, this paper presents an alternative for channel assessment on top of a commercial software-defined radio platform. Although there exist software solutions for performing spectrum sensing on such platforms, to the best of our knowledge, continuous spectrum sensing and long-term recording remain challenging. We propose a pioneering solution that is capable of seamless spectrum sensing over a wide spectrum band and guarantees sufficient flexibility in terms of configurations. The proposed solution is validated experimentally. We demonstrate two advantages of seamless spectrum sensing: the capability of accurate channel occupancy measurement and detecting transient signals such as Bluetooth.
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