Kinerja Spectrum Sensing Dengan Metode Cyclostationary Feature Detector Pada Radio Kognitif

HENDRY CAHYO, DWI ARYANTA, NASRULLAH ARMI

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ABSTRAK

Perkembangan dalam dunia telekomunikasi nirkabel terutama spektrum frekuensi adalah hal yang perlu mendapatkan perhatian penting. Spektrum frekuensi merupakan sumber daya yang terbatas, penggunaannya harus dilakukan secara efisien dan se-maksimal mungkin. Penelitian ini membahas teknik spectrum sensing pada radio kognitif untuk menghadapi masalah keterbatasan penggunaan spektrum frekuensi. Radio kognitif merupakan sistem radio cerdas yang bisa mengatur parameternya seperti frekuensi kerja, daya pancar, dan skema modulasi secara optimal dalam melakukan proses komunikasi. Spectrum sensing merupakan teknik untuk memaksimalkan penggunaan spektrum frekuensi. Penelitian ini membandingkan kinerja metode cyclostationary feature detection dan metode energy detection pada teknik spectrum sensing menggunakan software matlab sehingga dapat diketahui bahwa kinerja cyclostationary feature detection untuk nilai Pd = 0,85 lebih handal sebesar 0,2 untuk fungsi probability of false dan lebih handal sebesar 2 dB untuk fungsi signal to noise ratio daripada energy detection.

Kata kunci: radio kognitif, spectrum sensing, cyclostationary feature detection, energy detection, probability of false alarm.

 

ABSTRACT

Developments in the world of wireless telecommunications specially frequency spectrum is an important thing to get attention. Frequency spectrum is afinite resource, its use must be efficiently and as maximum as possible. This study discuss the technique of spectrum sensing in cognitive radio to faces the problem using restrictiveness of frequency spectrum. Cognitive radio is a smart radio system that can adjust its parameters like work frequency, emission power, and modulation scheme are optimal in the communication process. Spectrum sensing is a technique to maximize the use of the frequency spectrum. This study compared performance of cyclostationary feature detection methodh with energy detection methodh in spectrum sensing technique using matlab software so ascertainable that cyclostationary feature detection performance for Pd value 0,85 better about 0,2 for probability of false alarm function and better about 2 dB for signal to noise ratio function than energy detection.

Keywords:  cognitif radio, spectrum sensing, cyclostationary feature detection, energy detection, probability of false alarm.


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Referensi


Verma, Pradeep Kumar. (2012). Performance analysis of Energy detection, Matched filter detection & Cyclostationary feature detection Spectrum Sensing Techniques, Vol. 2, No. 5, pp : 1296-1301.

Subhedar, Mansi and Gajanan Birajdar. (2011). Spectrum Sensing Techniques in Cognitive Radio Networks: a Survey. India: Department of Electronics and Telecommunication Engineering, SIES Graduate School of Technology, Navi Mumbai.

Alaydrus, Mudrik. (2010). Cognitif Radio : Sistem Radio Cerdas. Jakarta : Magister Teknik Elektro, Universitas Mercu Buana.

Kim, Hyung Seok and Waleed Ejaz etc. (2013). I3S : Intelligent spectrum sensing scheme for cognitive radio networks, pp : 1499-1687.

Sood, Vishakha and Manwinder Singh. (2011). On the Performance of Detection based Spectrum Sensing for Cognitive Radio. India : Rayat Institute of Engineering and Information Technology, Railmajra, Punjab.




DOI: https://doi.org/10.26760/elkomika.v1i1.26

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