Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform

The static spectrum allocation policy in Malaysia and the rapid growth of wireless communication services have led to spectrum scarcity problem. Consequently, the Quality of Service (QoS) for new wireless services might be compromised as most of the radio bands are already assigned to licensed users...

Full description

Bibliographic Details
Main Author: Tahir, Nurizan (Author)
Format: Thesis
Published: 2018-01.
Subjects:
Online Access:Get fulltext
LEADER 01888 am a22001573u 4500
001 78940
042 |a dc 
100 1 0 |a Tahir, Nurizan  |e author 
245 0 0 |a Optimal spectrum sensing for cognitive radio network utilizing software defined radio platform 
260 |c 2018-01. 
520 |a The static spectrum allocation policy in Malaysia and the rapid growth of wireless communication services have led to spectrum scarcity problem. Consequently, the Quality of Service (QoS) for new wireless services might be compromised as most of the radio bands are already assigned to licensed users. But, the spectrum occupancy's measurement shows that the allocated spectrum is underutilized. Therefore, in this project, Opportunistic Spectrum Access (OSA) scheme is used to overcome the spectrum scarcity problem. The concept of OSA in cognitive radio technology is used to exploit the spectrum by permitting the secondary user to temporally use the licensed spectrum band when it is free. Hence, spectrum sensing is very important for the secondary user to avoid harmful interference to other wireless services. This project specifically will develop an optimal spectrum sensing mechanism using Particle Swarm Optimization (PSO) algorithm on Software Defined Radio (SDR) using platform called Universal Software Radio Peripheral (USRP). The data has been analysed to validate the performance of the spectrum sensing mechanism referring to the Probability of Detection (Pd) and Probability of False Alarm (Pf). The result shows that the optimal throughput is 93% for Pd 90%, SNR of 1.5dB and Pf 5% which is an improvement of 14% compared with non-optimal method. 
546 |a en 
650 0 4 |a TK Electrical engineering. Electronics Nuclear engineering 
655 7 |a Thesis 
787 0 |n http://eprints.utm.my/id/eprint/78940/ 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/78940/1/NurizanTahirMFKE2018.pdf