Performance Evaluation of Collaborative Sensing Cognitive Radio

Hagar Omar Shazly;

Abstract


Nowadays, Cognitive Radio Network (CRNs) becomes an emerging and rising technology which uses spectrum utilization more efficiently through spectrum sharing between licensed users (primary users (PU)) and unlicensed users (secondary users (SU)). One of the most challenging tasks in CRN is spectrum sensing (SS), which is facing problems like shadowing and fading. In these cases, SU cannot distinguish between a free band and a deep fading. Thus, collaborative SS is proposed to enhance the sensing performance. This thesis focuses on the performance of collaborative SS over Nakagami-m faded channel. Besides, it concentrates on this performance in case of non-faded AWGN channel in CR while malicious users are present. Furthermore, this thesis discusses the performance of collaborative SS over composite multipath fading and shadowing using K faded channel in the presence of malicious users. Moreover, it illustrates that SS gives better performance when more CR users cooperate.
This thesis presents a comparison between the collaborative sensing through faded channel (Nakagami-m model) and AWGN channel based on fusion rule which is defined by q out of ns rule.

This thesis deals with wireless security on the upper layers through encryption and authentication. However, for more effective performance of the SS, CR networks depend heavily on the physical layer because it is considered as a vulnerable hole to protect from any attack. This thesis investigates the security of CRNs by considering a physical security threat on SS and studies the performance of the CR system under channel impairments and malicious users (who can report false information in collaborative sensing).

In this thesis, analytical and numerical methods are used to investigate the performance of the collaborative sensing in cognitive radio networks under malicious attacks over different channel impairments. It illustrates the most suitable individual probability of detection in a real faded channel by using Nakagami-m model.

The presented work performs a reduction of operation parameter to get the suitable probability of detection against malicious attack in real faded channel using Nakagami-m model. Furthermore, it concentrates on more reliable channel attitude which includes the


Other data

Title Performance Evaluation of Collaborative Sensing Cognitive Radio
Other Titles تقويم أداء منظومة الاجهزة للاسلكية الادراكية ذات الاستشعار المجمع
Authors Hagar Omar Shazly
Issue Date 2017

Attached Files

File SizeFormat
J4289.pdf1.05 MBAdobe PDFView/Open
Recommend this item

Similar Items from Core Recommender Database

Google ScholarTM

Check

views 3 in Shams Scholar


Items in Ain Shams Scholar are protected by copyright, with all rights reserved, unless otherwise indicated.