Murti, Budi Bayu and Hidayat, Risanuri and Wibowo, Sigit Basuki (2021) Spectrum Sensing Using Adaptive Threshold Based Energy Detection in Cognitive Radio System. In: 2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 16-17 December 2021, Yogyakarta.
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Wireless communication has experienced rapid development and has been widely used to meet the needs of society. However, in some real situations it shows that most of the allocated radio frequency spectrum is underutilized. Cognitive radio (CR) system is a smart technology that goals to improve the utilization of licensed spectrum frequencies by providing effective access to Secondary Users (SU). Dynamic spectrum access techniques can be used without intervention to the Primary User (PU). The main problem in CR is the sensing of the spectrum which must be able to accurately ensured the presence of a primary user signal in the licensed frequency band. In this research, a framework was conducted and developed based on the modeling of spectrum energy detection. Modeling is done on the PU signal source, AWGN communication channel, as well as the SU receiver side. Evaluation is carried out to obtain adaptive threshold value settings that can be adjusted to obtain optimum detection. Results analysis was performed statistically based on ROC graphs to determine the performance of the detection system. The results of the simulation showed that at the Pfa value that has been set, then the value of Pd will increase along with the increase in the value of SNR. The value of Pd also increase with the number of samples used. At the level of Pfa=0.1, from 500 to 1500 samples the probability of detection increases to 48 . © 2021 IEEE.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Cited by: 6 |
Uncontrolled Keywords: | Radio systems; Signal receivers; Signal to noise ratio; Spectroscopy; Adaptive thresholds; Energy detection; Primary Users; Radio frequency spectrum; Real situation; ROC; Secondary user; SNR; Spectrum sensing; Wireless communications; Cognitive radio |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering > Electrical and Information Technology Department |
Depositing User: | Sri JUNANDI |
Date Deposited: | 25 Oct 2024 09:12 |
Last Modified: | 25 Oct 2024 09:12 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/8563 |