Orthogonal frequency division multiplexing based cognitive radio using GNU radio and universal software radio peripheral
The current development of wireless communication infrastructures and technologies have caused frequency spectrum to become scarce. It is also found that underutilization of spectrum occurred on conventional fixed spectrum management policy. Therefore, lots of research has been done to utilize these...
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/48019/25/SeeWenXingMFKE2014.pdf |
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| Summary: | The current development of wireless communication infrastructures and technologies have caused frequency spectrum to become scarce. It is also found that underutilization of spectrum occurred on conventional fixed spectrum management policy. Therefore, lots of research has been done to utilize these spectrum in an efficient manner by opportunistically exploiting the underutilize incumbent's spectrum. Cognitive Radio (CR) has been introduced as a promising way to utilize this unused spectrum through frequency, time and space domain. The main functionalities of CR are spectrum sensing, spectrum management, spectrum mobility and self-learning. To support high data transmission rate, Orthogonal Frequency Division Multiplexing (OFDM) with flexible modulation and high spectral efficiency has been considered. In this thesis, an experimental Software Defined Radio (SDR) platform which consists of GNU Radio and Universal Software Radio Peripheral version two (USRP2) are developed for OFDM-based CR system as proof-of-concept. Edge Energy Detection (EED) as a new joint sensing decision mechanism between Energy Detection (ED) and Edge Detection is proposed to improve the sensitivity of spectrum sensing. The experimental work is carried out in an ad-hoc network which resulted in time and frequency synchronization between nodes becoming crucial task. Therefore, Time Division Multiple Access (TDMA) and Carrier Sense Multiple Access (CSMA) protocols are deployed to ensure reliable communication system is achieved. Furthermore, Reinforcement Learning (RL) concept is adopted in this system for self-learning of the surrounding radio environment. The results showed: performance metrics in term of probability of false alarm ( ) and probability of detection ( ) for EED are improved by 10% as compared to ED and Edge Detection; CSMA-RL decreases the total number of collision by 50% over CSMA; and the number of data packets loss is decreased during switching transitions. Finally, the proposed system is evaluated with multimedia data transmission applications and results show the throughput and other performance metrics are significantly improved. In conclusion, this proposed CR system is proven beneficial for future communication technology in term of spectrum utilization. |
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