Spektrin Havainnointi Kognitiivisissa Matkaviestinlaitteissa

Radio spectrum is becoming a scarce resource as increasing number of wireless devices attempt to access it. As a solution to this issue, spectrum sensing based cognitive radios have been proposed. However, significant part of them are mobile, consumer-grade devices that have strict price and form-factor limitations. This works aims to address the issues related to mobile spectrum sensing by characterizing the non-idealities with a spectrum sensor prototype. Two efficient sensing algorithms and a coarse-fine controller, which aims to minimize the energy consumption and run time of an individual sensor, are implemented on an FPGA. Functionality of the implementations is verified by laboratory and field measurements. Finally, a spatial interpolation method, Kriging, is applied to the non-ideal measurement data to create a uniform radio environment map.Langattomien laitteiden yleistyminen kasvattaa radiospektrin käyttöastetta ylärajaa kohti. Ratkaisuksi ongelmaan on kehitetty spektrin havainnointiin perustuvat kognitiiviset radiot. Näistä valtaosa on kuitenkin kuluttajatason matkaviestinlaitteita, joilla on tiukat rajoitteet muun muassa hinnan ja fyysisen rakenteen suhteen. Tässä työssä perehdytään spektrin havainnoinnin haasteisiin tutkimalla havainnoinnin epäideaalisuuksia spektrisensoriprototyypillä. Työssä on toteutettu FPGA:lle kaksi energiatehokasta havainnointialgoritmia sekä karkea-herkkä -ohjain, joka pyrkii minimoimaan yksittäisen spektrisensorin energiakulutusta sekä havainnointiaikaa. Toteutettujen algoritmien toiminta ja suorituskyky verifioidaan laboratorio- sekä kenttämittauksilla. Lopuksi esitellään avaruudellinen interpolaatiomenetelmä, Kriging, jota sovelletaan epäideaaliseen kenttämittausdataan kattavan radiopeitekartan luomiseksi

Digital Linearization of Direct-Conversion Spectrum Sensing Receiver

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Spatial Interpolation of Cyclostationary Test Statistics in Cognitive Radio Networks

The focus of this paper is on evaluating different spatial interpolation methods for the construction of radio environment map (REM) using field measurements obtained by cyclostationary based mobile sensors. Mobile sensing devices employing cyclostationary detectors provide lot of advantages compared to widely used energy detectors such as robustness to noise uncertainty and ability to distinguish among different primary user signals. However, mobile sensing results are not available at locations between the sensors making it difficult for a secondary user (possibly without a spectrum sensor) to decide whether or not to use primary user resources at that location. To overcome this, spatial interpolation of test statistics measured at limited number of locations can be carried out to create a channel occupancy map at unmeasured locations between the sensors. For this purpose, different spatial interpolation techniques for the cyclostationary test statistic have been employed in this paper such as inverse distance weighting (IDW), ordinary Kriging (OK), and universal Kriging (UK). The effectiveness of these methods is demonstrated by applying them on extensive real-world field measurement data obtained by mobile-phone-compliant spectrum sensors. The field measurements were carried out using four mobile spectrum sensors measuring eight DVB-T channels at more than hundred locations encompassing roughly one-third of the area of the city of Espoo in Finland. The accuracy of the spatial interpolation results based on the field measurements is determined using the cross validation approach with the widely used root mean square error (RMSE) as the metric. Field measurement results indicate that reliable results with spatial coverage can be achieved using Kriging for cyclostationary based test statistics. Comparison of spatial interpolation results of cyclostationary test statistics is also carried out with those of energy values obtained during the measurement campaign in the form of received signal strength indicator (RSSI). Comparison results clearly show the performance improvement and robustness obtained by the use of cyclostationary based detectors instead of energy detectors.Peer reviewe