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Performance Evaluation of Cyclostationary-Based Cooperative Sensing Using Field Measurements | IEEE Journals & Magazine | IEEE Xplore

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 cooperativ...Show More

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 scena...
Published in: IEEE Transactions on Vehicular Technology ( Volume: 65, Issue: 4, April 2016)
Page(s): 1982 - 1997
Date of Publication: 13 April 2015

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I. Introduction

Proliferation of wireless devices and services, the need for higher data rates, and policy of fixed spectrum allocation have resulted in shortage of frequency resources for communication. This problem can be alleviated by using cognitive radios capable of dynamic spectrum access so that secondary users (SUs) can utilize resources temporarily unused by a primary user (PU) [1], [2]. However, this secondary access of the spectrum is on the condition that the interference caused to the PUs is strictly controlled and managed. Therefore, sensing, i.e., the process of gathering awareness about the surrounding radio environment, is essential for cognitive radios [2]– [4]. In addition to identifying idle spectrum and enabling cognitive communication, sensing can be also used to manage interference in wireless networks and to improve the spatial–temporal resolution and accuracy of the spectrum allocation databases.

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