<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to improve spectrum utilization rate, people need a method to sense the spectrum hole. This article puts forward a spectrum sensing algorithm, which uses ATSC DTV signal structural characteristics. First, we should sample the input signal based on structural characteristics. Second, these signal samples should be separated into different sets and accumulate these samples. Third, we execute the correlation operation to accumulation result and synchronization. Finally, decision can be got by comparing the test statistics with threshold. According to the simulation result, we can get the conclusion that signal structural characteristics based on spectrum sensing method can realize spectrum sensing well enough.</p></abstract>

In order to improve spectrum utilization rate, people need a method to sense the spectrum hole. This article puts forward a spectrum sensing algorithm, which uses ATSC DTV signal structural characteristics. First, we should sample the input signal based on structural characteristics. Second, these signal samples should be separated into different sets and accumulate these samples. Third, we execute the correlation operation to accumulation result and synchronization. Finally, decision can be got by comparing the test statistics with threshold. According to the simulation result, we can get the conclusion that signal structural characteristics based on spectrum sensing method can realize spectrum sensing well enough.

Spectrum Sensing Algorithm Based on ATSC DTV Signal Structure

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Spectrum Sensing Algorithm Based on ATSC DTV Signal Structure"}

In order to improve spectrum utilization rate, people need a method to sense the spectrum hole. This article puts forward a spectrum sensing algorithm, which...

Spectrum Sensing Algorithm Based on ATSC DTV Signal Structure

Online veröffentlicht: 16. Dez. 2013

Seitenbereich: 2136 - 2154

Eingereicht: 13. Aug. 2013

Akzeptiert: 17. Nov. 2013

DOI: https://doi.org/10.21307/ijssis-2017-631

© 2013 Yuliang Cong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.