A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network

In 5G systems, enhancing the energy efficiency (EE) and spectrum efficiency (SE) is a significant task that is capable of fulfilling the demand of future wireless networks and providing Quality of Service (QoS) provisioning, such as high throughput with low power consumption. In the present work, a...

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Main Authors: Osamah Ibrahim Khalaf, Kingsley A. Ogudo, Manwinder Singh
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/13/1/47
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spelling doaj-975670ca7d184b99bf246e262dc1bbbc2020-12-31T00:04:13ZengMDPI AGSymmetry2073-89942021-12-0113474710.3390/sym13010047A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G NetworkOsamah Ibrahim Khalaf0Kingsley A. Ogudo1Manwinder Singh2Al-Nahrain Nanorenewable Energy Research Centre (NNERC), AI-Nahrain University, Baghdad 64074, IraqDepartment of Electrical and Electronics Engineering, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2092, South AfricaDepartment of ECE, Faculty of Engineering, Lovely Professional University, Jalandhar, Punjab 144001, IndiaIn 5G systems, enhancing the energy efficiency (EE) and spectrum efficiency (SE) is a significant task that is capable of fulfilling the demand of future wireless networks and providing Quality of Service (QoS) provisioning, such as high throughput with low power consumption. In the present work, a look-up table enabled a fuzzy-based approach to investigate the SE and EE issues in 5G networks and obtained an efficient symmetrical trade-off between them to enhance the system’s overall performance. We completed simulations in NS-2.31 software version 2.31, and MATLAB is used to visualize the results. The proposed model achieved maximum values of EE and SE of 0.92 bit/J/Hz with a sensing time τ<sub>s(LUT)</sub> = 20 ms. Furthermore, optimizing the sensing time and the secondary user (SU) transmission power, yielded a maximum EE and provided a QoS provisioned cognitive radio-enabled 5G network.https://www.mdpi.com/2073-8994/13/1/47cognitive radios (CR)co-operative spectrum sensing (CSS)quality of service provisioninglook-up table (LUT)energy harvesting (EH)energy efficiency
collection DOAJ
language English
format Article
sources DOAJ
author Osamah Ibrahim Khalaf
Kingsley A. Ogudo
Manwinder Singh
spellingShingle Osamah Ibrahim Khalaf
Kingsley A. Ogudo
Manwinder Singh
A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network
Symmetry
cognitive radios (CR)
co-operative spectrum sensing (CSS)
quality of service provisioning
look-up table (LUT)
energy harvesting (EH)
energy efficiency
author_facet Osamah Ibrahim Khalaf
Kingsley A. Ogudo
Manwinder Singh
author_sort Osamah Ibrahim Khalaf
title A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network
title_short A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network
title_full A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network
title_fullStr A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network
title_full_unstemmed A Fuzzy-Based Optimization Technique for the Energy and Spectrum Efficiencies Trade-Off in Cognitive Radio-Enabled 5G Network
title_sort fuzzy-based optimization technique for the energy and spectrum efficiencies trade-off in cognitive radio-enabled 5g network
publisher MDPI AG
series Symmetry
issn 2073-8994
publishDate 2021-12-01
description In 5G systems, enhancing the energy efficiency (EE) and spectrum efficiency (SE) is a significant task that is capable of fulfilling the demand of future wireless networks and providing Quality of Service (QoS) provisioning, such as high throughput with low power consumption. In the present work, a look-up table enabled a fuzzy-based approach to investigate the SE and EE issues in 5G networks and obtained an efficient symmetrical trade-off between them to enhance the system’s overall performance. We completed simulations in NS-2.31 software version 2.31, and MATLAB is used to visualize the results. The proposed model achieved maximum values of EE and SE of 0.92 bit/J/Hz with a sensing time τ<sub>s(LUT)</sub> = 20 ms. Furthermore, optimizing the sensing time and the secondary user (SU) transmission power, yielded a maximum EE and provided a QoS provisioned cognitive radio-enabled 5G network.
topic cognitive radios (CR)
co-operative spectrum sensing (CSS)
quality of service provisioning
look-up table (LUT)
energy harvesting (EH)
energy efficiency
url https://www.mdpi.com/2073-8994/13/1/47
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