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A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network

Doctor of Philosophy in Communication Engineering

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Bibliographic Details
Main Author: Mohammad Nayeem, Morshed
Other Authors: Sabira, Khatun, Prof. Dr.
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2017
Subjects:
Cognitive radio networks
Wireless LANs
Spectrum saturation
Frequency spectrum
Spectrum detection
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72569
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spelling my.unimap-725692021-12-17T03:23:11Z A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network Mohammad Nayeem, Morshed Sabira, Khatun, Prof. Dr. Cognitive radio networks Wireless LANs Spectrum saturation Frequency spectrum Spectrum detection Doctor of Philosophy in Communication Engineering Spectrum saturation problem is a critical issue now a day due to huge number of users with wireless capable devices joined the network every day, but the spectrum resources are limited. To overcome this issue, cognitive radio (CR) technology was first proposed in year of 1999. The main objective of CR is to use licensed primary users’ (PUs’) spectrum by secondary users (SUs) without interfering the PUs. To detect PU channels, spectrum detection technique plays a major role to find the presence or absence of PUs to avoid interference. To protect licensed PUs’ from unwanted interference, the channel detection scheme is required to perform well in low signal to noise ratio (SNR) environments. Most of the work in the literature were performed based on computer based simulations and very few with experimental workflow, but they have used heavy laboratory instruments or stationary sensors for channel detection. Considering this issue, this thesis presents a method for real-time channel detection technique in a wireless local area network (WLAN) based CR network using Android based smartphones/tablet PCs. Also, designed an automatic channel selection (ACS) algorithm, which is practically experimented with an adaptive threshold determination technique with the 2.4 GHz WLAN. The algorithm is designed to work especially with Android based smartphones and tablets. Energy detection method with free space path loss (FSPL) environment is considered throughout the experiment for available PU channel detection. 2017 2021-10-21T02:33:22Z 2021-10-21T02:33:22Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72569 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Cognitive radio networks
Wireless LANs
Spectrum saturation
Frequency spectrum
Spectrum detection
spellingShingle Cognitive radio networks
Wireless LANs
Spectrum saturation
Frequency spectrum
Spectrum detection
Mohammad Nayeem, Morshed
A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
description Doctor of Philosophy in Communication Engineering
author2 Sabira, Khatun, Prof. Dr.
author_facet Sabira, Khatun, Prof. Dr.
Mohammad Nayeem, Morshed
format Thesis
author Mohammad Nayeem, Morshed
author_sort Mohammad Nayeem, Morshed
title A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
title_short A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
title_full A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
title_fullStr A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
title_full_unstemmed A resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
title_sort resilient cognitive detection with automated channel selection for enhanced channel management in wireless local area network
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2017
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72569
_version_ 1724609922444820480
score 13.223943

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