Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks

Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Bibliografiske detaljer
Main Authors: Sarker, Pramit Likhan, Salama, Umme
Andre forfattere: Chakrabarty, Amitabha
Format: Thesis
Sprog:English
Udgivet: BRAC University 2018
Fag:
Spectrum sensing
Signal-to-noise ratio
Primary user signal
Energy threshold
Online adgang:http://hdl.handle.net/10361/10132
id 10361-10132
record_format dspace
spelling 10361-101322022-01-26T10:04:57Z Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks Sarker, Pramit Likhan Salama, Umme Chakrabarty, Amitabha Department of Computer Science and Engineering, BRAC University Spectrum sensing Signal-to-noise ratio Primary user signal Energy threshold This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 45-46). Cognitive Radio (CR) deals with the designing of intelligent wireless communication systems through the use of transceivers that are capable of automatically detecting and accessing vacant communication channels in the radio bandwidth while avoiding the ones occupied, with the aim of maximizing the utilization of the Radio Frequency (RF) spectrum and minimizing the interference of users. In primary transmitter detection i.e. non-cooperative spectrum sensing, the licensed primary users (PUs) are detected based on the signal received by the unlicensed secondary users (SUs). This paper provides an insight into one such method, namely, the energy detection technique, which has low computational and implementation complexities, and is extremely generic. However, the detection of weak PU signals across a noisy channel is a challenging endeavor and calls for a more sophisticated approach. A matched filter can be used to obtain additional information regarding the channel activity, help individuate the transmitted pulses from the noise and reduce the effects of unlicensed signal interference. The proposed algorithm attains results from a matched filter and implements it within the energy detector, analyzing the signals over an Additive White Gaussian Noise (AWGN) channel for a range of Signal-to-Noise Ratios (SNRs), which are then evaluated through Receiver Operating Characteristic (ROC) curves with probability of detection (Pd) and probability of false alarm (Pf) as performance metrics. Pramit Likhan Sarker Umme Salama B. Computer Science and Engineering 2018-05-13T06:07:13Z 2018-05-13T06:07:13Z 2018 2018-04 Thesis ID 13201073 ID 14101041 http://hdl.handle.net/10361/10132 en BRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 46 pages application/pdf BRAC University
institution Brac University
collection Institutional Repository
language English
topic Spectrum sensing
Signal-to-noise ratio
Primary user signal
Energy threshold
spellingShingle Spectrum sensing
Signal-to-noise ratio
Primary user signal
Energy threshold
Sarker, Pramit Likhan
Salama, Umme
Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
description This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
author2 Chakrabarty, Amitabha
author_facet Chakrabarty, Amitabha
Sarker, Pramit Likhan
Salama, Umme
format Thesis
author Sarker, Pramit Likhan
Salama, Umme
author_sort Sarker, Pramit Likhan
title Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
title_short Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
title_full Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
title_fullStr Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
title_full_unstemmed Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
title_sort enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks
publisher BRAC University
publishDate 2018
url http://hdl.handle.net/10361/10132
work_keys_str_mv AT sarkerpramitlikhan enhancedenergydetectionusingmatchedfilterforspectrumsensingincognitiveradionetworks
AT salamaumme enhancedenergydetectionusingmatchedfilterforspectrumsensingincognitiveradionetworks
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