Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements

Research output: Contribution to journalArticleScientificpeer-review

Standard

Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements. / Chaudhari, Sachin; Kosunen, Marko; Mäkinen, Semu; Oksanen, Jan; Laatta, Markus; Ojaniemi, Jaakko; Koivunen, Visa; Ryynänen, Jussi; Valkama, Mikko.

In: IEEE Transactions on Vehicular Technology, Vol. 65, No. 4, 7084673, 01.04.2016, p. 1982-1997.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

APA

Chaudhari, S., Kosunen, M., Mäkinen, S., Oksanen, J., Laatta, M., Ojaniemi, J., ... Valkama, M. (2016). Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements. IEEE Transactions on Vehicular Technology, 65(4), 1982-1997. [7084673]. https://doi.org/10.1109/TVT.2015.2422715

Vancouver

Author

Chaudhari, Sachin ; Kosunen, Marko ; Mäkinen, Semu ; Oksanen, Jan ; Laatta, Markus ; Ojaniemi, Jaakko ; Koivunen, Visa ; Ryynänen, Jussi ; Valkama, Mikko. / Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements. In: IEEE Transactions on Vehicular Technology. 2016 ; Vol. 65, No. 4. pp. 1982-1997.

Bibtex - Download

@article{bf58ffc583444f7593948e003cb92a3e,
title = "Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements",
abstract = "This paper focuses on evaluating the gains obtained through cooperative spectrum sensing in the real world while using cyclostationary-based mobile sensors. In cooperative sensing (CS), different secondary users (SUs) in a geographical neighborhood cooperate to detect the presence of a primary user (PU). Compared with single-user sensing, cooperation provides diversity gains in the face of multipath fading and shadowing. The effectiveness of CS is demonstrated by analyzing data acquired in two extensive field measurement campaigns. The first measurement campaign (MC-I) focuses on measurements at fixed locations, whereas the second measurement campaign (MC-II) focuses on a scenario where measurements are taken inside a moving car. These measurements are carried out for DVB-T channels in the Capital Region of Finland, which consists of urban and suburban environments. Hard decision rules such as or, and, and majority and a soft decision rule such as sum of cyclostationary test statistics (sum) are employed, and their detection performances are compared with a cyclostationary-based single-user detector. A performance parameter of relative increase in probability of detection (RIPD) is used to efficiently demonstrate the cooperation gain obtained relative to local sensing. It is shown that cooperation can significantly improve the performance of a sensor severely affected by fading and shadowing effects. Furthermore, it is shown that increasing the number of collaborating users beyond few users (five to eight) does not, in practice, bring significant improvement in terms of the expected RIPD. The performances of CS schemes evaluated from MC-I are also compared with the corresponding simulated CS results using empirical channel models and terrain data for the same experimental parameters. It is shown that the use of empirical or theoretical models may result in detection errors in practical conditions, and measurements should be used to improve the accuracy in such scenarios.",
keywords = "Cognitive radios, Cooperative detection, Cyclostationary detectors, Field measurements, Mobile sensors",
author = "Sachin Chaudhari and Marko Kosunen and Semu M{\"a}kinen and Jan Oksanen and Markus Laatta and Jaakko Ojaniemi and Visa Koivunen and Jussi Ryyn{\"a}nen and Mikko Valkama",
year = "2016",
month = "4",
day = "1",
doi = "10.1109/TVT.2015.2422715",
language = "English",
volume = "65",
pages = "1982--1997",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
number = "4",

}

RIS - Download

TY - JOUR

T1 - Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements

AU - Chaudhari, Sachin

AU - Kosunen, Marko

AU - Mäkinen, Semu

AU - Oksanen, Jan

AU - Laatta, Markus

AU - Ojaniemi, Jaakko

AU - Koivunen, Visa

AU - Ryynänen, Jussi

AU - Valkama, Mikko

PY - 2016/4/1

Y1 - 2016/4/1

N2 - This paper focuses on evaluating the gains obtained through cooperative spectrum sensing in the real world while using cyclostationary-based mobile sensors. In cooperative sensing (CS), different secondary users (SUs) in a geographical neighborhood cooperate to detect the presence of a primary user (PU). Compared with single-user sensing, cooperation provides diversity gains in the face of multipath fading and shadowing. The effectiveness of CS is demonstrated by analyzing data acquired in two extensive field measurement campaigns. The first measurement campaign (MC-I) focuses on measurements at fixed locations, whereas the second measurement campaign (MC-II) focuses on a scenario where measurements are taken inside a moving car. These measurements are carried out for DVB-T channels in the Capital Region of Finland, which consists of urban and suburban environments. Hard decision rules such as or, and, and majority and a soft decision rule such as sum of cyclostationary test statistics (sum) are employed, and their detection performances are compared with a cyclostationary-based single-user detector. A performance parameter of relative increase in probability of detection (RIPD) is used to efficiently demonstrate the cooperation gain obtained relative to local sensing. It is shown that cooperation can significantly improve the performance of a sensor severely affected by fading and shadowing effects. Furthermore, it is shown that increasing the number of collaborating users beyond few users (five to eight) does not, in practice, bring significant improvement in terms of the expected RIPD. The performances of CS schemes evaluated from MC-I are also compared with the corresponding simulated CS results using empirical channel models and terrain data for the same experimental parameters. It is shown that the use of empirical or theoretical models may result in detection errors in practical conditions, and measurements should be used to improve the accuracy in such scenarios.

AB - This paper focuses on evaluating the gains obtained through cooperative spectrum sensing in the real world while using cyclostationary-based mobile sensors. In cooperative sensing (CS), different secondary users (SUs) in a geographical neighborhood cooperate to detect the presence of a primary user (PU). Compared with single-user sensing, cooperation provides diversity gains in the face of multipath fading and shadowing. The effectiveness of CS is demonstrated by analyzing data acquired in two extensive field measurement campaigns. The first measurement campaign (MC-I) focuses on measurements at fixed locations, whereas the second measurement campaign (MC-II) focuses on a scenario where measurements are taken inside a moving car. These measurements are carried out for DVB-T channels in the Capital Region of Finland, which consists of urban and suburban environments. Hard decision rules such as or, and, and majority and a soft decision rule such as sum of cyclostationary test statistics (sum) are employed, and their detection performances are compared with a cyclostationary-based single-user detector. A performance parameter of relative increase in probability of detection (RIPD) is used to efficiently demonstrate the cooperation gain obtained relative to local sensing. It is shown that cooperation can significantly improve the performance of a sensor severely affected by fading and shadowing effects. Furthermore, it is shown that increasing the number of collaborating users beyond few users (five to eight) does not, in practice, bring significant improvement in terms of the expected RIPD. The performances of CS schemes evaluated from MC-I are also compared with the corresponding simulated CS results using empirical channel models and terrain data for the same experimental parameters. It is shown that the use of empirical or theoretical models may result in detection errors in practical conditions, and measurements should be used to improve the accuracy in such scenarios.

KW - Cognitive radios

KW - Cooperative detection

KW - Cyclostationary detectors

KW - Field measurements

KW - Mobile sensors

UR - http://www.scopus.com/inward/record.url?scp=84964838650&partnerID=8YFLogxK

U2 - 10.1109/TVT.2015.2422715

DO - 10.1109/TVT.2015.2422715

M3 - Article

VL - 65

SP - 1982

EP - 1997

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 4

M1 - 7084673

ER -

ID: 2007856