S p ati al I nt er p ol ati o n of C y cl ost ati o n ar y T est St atisti cs i n C o g niti v e R a di o N et w or ks: M et h o ds a n d Fi el d M e as ur e m e nts S a c hi n C h a u d h ari , M e m b er, I E E E, M ar k o K os u n e n , M e m b er, I E E E, S e m u Mä ki n e n, C h a n dr as e k ar a n R a m a n at h a n, J a n O ks a n e n , M e m b er, I E E E, M ar k us L a att a , St u d e nt M e m b e r, I E E E, J ussi R y y nä n e n , M e m b er, I E E E, Vis a K oi v u n e n , F ell o w, I E E E, a n d Mi k k o V al k a m a , S e ni or M e m b er, I E E E
This paper focuses on evaluating the gains obtained through cooperative spectrum sensing in 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). As compared to single-user sensing, cooperation provides diversity gains in the face of multipath fading and shadowing. The effectiveness of the 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 while 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 Finland's Capital Region, which consists of urban and suburban environments. Hard decision rules such as OR, AND, MAJORITY and soft decision rule such as SUM (sum of cyclostationary test statistics) are employed and their detection performances are compared to 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 (5-8) 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 to 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.
Spectrum sensing is a key component for obtaining spectrum awareness required for dynamic spectrum access in cognitive radio networks. It helps in finding spectrum opportunities for the secondary user (SU) while managing the interference to the primary user (PU). The performance of single-user sensing degrades in the presence of multipath fading and shadowing. Cooperative sensing can overcome this issue by providing diversity gains. There are also added benefits of performance improvement and simpler detectors. Although there is lot of literature on cooperative sensing, there is still lack of measurement campaigns verifying the cooperative gains in practical scenarios using mobile sensors. In this paper, the gain of using cooperative sensing is evaluated based on the largescale measurement campaign carried out in Helsinki, Finland using six cyclostationary based mobile sensors measuring over 100 locations. The measurements are carried out for 16 DVB-T channels with bandwidth of 8 MHz each. Fusion rules such as OR, AND, MAJORITY, and SUM (of cyclostationary based local test statistics) are employed and their performances compared to a cyclostationary based local detector. The results demonstrate the gains obtained by cooperative sensing based on the real-world field measurements using mobile sensors.
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