Spatial Interpolation of Cyclostationary Test Statistics in Cognitive Radio Networks: Methods and Field Measurements

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Spatial Interpolation of Cyclostationary Test Statistics in Cognitive Radio Networks : Methods and Field Measurements. / Chaudhari, Sachin; Kosunen, Marko; Mäkinen, Semu; Chandrasekaran, Ramanathan; Oksanen, Jan; Laatta, Markus; Ryynanen, Jussi; Koivunen, Visa; Valkama, Mikko.

In: IEEE Transactions on Vehicular Technology, Vol. 67, No. 2, 02.2018, p. 1113 - 1129.

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Chaudhari, Sachin ; Kosunen, Marko ; Mäkinen, Semu ; Chandrasekaran, Ramanathan ; Oksanen, Jan ; Laatta, Markus ; Ryynanen, Jussi ; Koivunen, Visa ; Valkama, Mikko. / Spatial Interpolation of Cyclostationary Test Statistics in Cognitive Radio Networks : Methods and Field Measurements. In: IEEE Transactions on Vehicular Technology. 2018 ; Vol. 67, No. 2. pp. 1113 - 1129.

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@article{97420321243f4ad8a42226e97af4394f,
title = "Spatial Interpolation of Cyclostationary Test Statistics in Cognitive Radio Networks: Methods and Field Measurements",
abstract = "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.",
keywords = "Cognitive radio, cyclostationary detection, Databases, Detectors, energy detection, Hardware, Interference, Interpolation, Kriging, Mobile communication, radio environment map, spatial estimation, spectrum sensing",
author = "Sachin Chaudhari and Marko Kosunen and Semu M{\"a}kinen and Ramanathan Chandrasekaran and Jan Oksanen and Markus Laatta and Jussi Ryynanen and Visa Koivunen and Mikko Valkama",
year = "2018",
month = "2",
doi = "10.1109/TVT.2017.2717379",
language = "English",
volume = "67",
pages = "1113 -- 1129",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
number = "2",

}

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TY - JOUR

T1 - Spatial Interpolation of Cyclostationary Test Statistics in Cognitive Radio Networks

T2 - Methods and Field Measurements

AU - Chaudhari, Sachin

AU - Kosunen, Marko

AU - Mäkinen, Semu

AU - Chandrasekaran, Ramanathan

AU - Oksanen, Jan

AU - Laatta, Markus

AU - Ryynanen, Jussi

AU - Koivunen, Visa

AU - Valkama, Mikko

PY - 2018/2

Y1 - 2018/2

N2 - 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.

AB - 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.

KW - Cognitive radio

KW - cyclostationary detection

KW - Databases

KW - Detectors

KW - energy detection

KW - Hardware

KW - Interference

KW - Interpolation

KW - Kriging

KW - Mobile communication

KW - radio environment map

KW - spatial estimation

KW - spectrum sensing

UR - http://www.scopus.com/inward/record.url?scp=85021845608&partnerID=8YFLogxK

U2 - 10.1109/TVT.2017.2717379

DO - 10.1109/TVT.2017.2717379

M3 - Article

AN - SCOPUS:85021845608

VL - 67

SP - 1113

EP - 1129

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 2

ER -

ID: 14525608