Mobile users are more and more requesting new value-added services, such as the localization services, anyway anywhere and anytime, even in hostile propagation environments, such as indoor scenarios. Here, we propose a fast and blind signal processing method to assess users' movements in indoor Wi-Fi communications on mobile devices. The contribution of our work is twofold. First, we determine the channel interference and select the Wi-Fi channel with the strongest received signal power. Then, we exploit this channel information to assess if a user is approaching or leaving an Access Point. We develop an application in Java, for Android-based mobile platforms. We test our method in real indoor environments, comparing our results with the ones obtained by commercial tools and recently published algorithms. The obtained outcomes show the efficiency of our approach in assessing users' movements in indoor scenarios.
Tedeschi, A., Benedetto, F., Paglione, L. (2015). A blind signal processing method for assessing users' movements in indoor Wi-Fi communications by Android-based smartphones. In 2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015 (pp.149-153). Institute of Electrical and Electronics Engineers Inc. [10.1109/TSP.2015.7296241].
A blind signal processing method for assessing users' movements in indoor Wi-Fi communications by Android-based smartphones
TEDESCHI, ANTONIO;BENEDETTO, FRANCESCO;Paglione, Luca
2015-01-01
Abstract
Mobile users are more and more requesting new value-added services, such as the localization services, anyway anywhere and anytime, even in hostile propagation environments, such as indoor scenarios. Here, we propose a fast and blind signal processing method to assess users' movements in indoor Wi-Fi communications on mobile devices. The contribution of our work is twofold. First, we determine the channel interference and select the Wi-Fi channel with the strongest received signal power. Then, we exploit this channel information to assess if a user is approaching or leaving an Access Point. We develop an application in Java, for Android-based mobile platforms. We test our method in real indoor environments, comparing our results with the ones obtained by commercial tools and recently published algorithms. The obtained outcomes show the efficiency of our approach in assessing users' movements in indoor scenarios.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
