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Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks

BACKGROUND: Wireless links are fast becoming the key communication mode. However, as compared to the wired link, their characteristics make the traffic prone to time- and location-dependent signal attenuation, noise, fading, and interference that result in time varying channel capacities and link er...

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Autores principales: Ashfaq, Khuram, Safdar, Ghazanfar Ali, Ur-Rehman, Masood
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157178/
https://www.ncbi.nlm.nih.gov/pubmed/34084939
http://dx.doi.org/10.7717/peerj-cs.546
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author Ashfaq, Khuram
Safdar, Ghazanfar Ali
Ur-Rehman, Masood
author_facet Ashfaq, Khuram
Safdar, Ghazanfar Ali
Ur-Rehman, Masood
author_sort Ashfaq, Khuram
collection PubMed
description BACKGROUND: Wireless links are fast becoming the key communication mode. However, as compared to the wired link, their characteristics make the traffic prone to time- and location-dependent signal attenuation, noise, fading, and interference that result in time varying channel capacities and link error rate. Scheduling algorithms play an important role in wireless links to guarantee quality of service (QoS) parameters such as throughput, delay, jitter, fairness and packet loss rate. The scheduler has vital importance in current as well as future cellular communications since it assigns resource block (RB) to different users for transmission. Scheduling algorithm makes a decision based on the information of link state, number of sessions, reserved rates and status of the session queues. The information required by a scheduler implemented in the base station can easily be collected from the downlink transmission. METHODS: This paper reflects on the importance of schedulers for future wireless communications taking LTE-A networks as a case study. It compares the performance of four well-known scheduling algorithms including round robin (RR), best channel quality indicator (BCQI), proportional fair (PF), and fractional frequency reuse (FFR). The performance of these four algorithms is evaluated in terms of throughput, fairness index, spectral efficiency and overall effectiveness. System level simulations have been performed using a MATLAB based LTE-A Vienna downlink simulator. RESULTS: The results show that the FFR scheduler is the best performer among the four tested algorithms. It also exhibits flexibility and adaptability for radio resource assignment.
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spelling pubmed-81571782021-06-02 Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks Ashfaq, Khuram Safdar, Ghazanfar Ali Ur-Rehman, Masood PeerJ Comput Sci Algorithms and Analysis of Algorithms BACKGROUND: Wireless links are fast becoming the key communication mode. However, as compared to the wired link, their characteristics make the traffic prone to time- and location-dependent signal attenuation, noise, fading, and interference that result in time varying channel capacities and link error rate. Scheduling algorithms play an important role in wireless links to guarantee quality of service (QoS) parameters such as throughput, delay, jitter, fairness and packet loss rate. The scheduler has vital importance in current as well as future cellular communications since it assigns resource block (RB) to different users for transmission. Scheduling algorithm makes a decision based on the information of link state, number of sessions, reserved rates and status of the session queues. The information required by a scheduler implemented in the base station can easily be collected from the downlink transmission. METHODS: This paper reflects on the importance of schedulers for future wireless communications taking LTE-A networks as a case study. It compares the performance of four well-known scheduling algorithms including round robin (RR), best channel quality indicator (BCQI), proportional fair (PF), and fractional frequency reuse (FFR). The performance of these four algorithms is evaluated in terms of throughput, fairness index, spectral efficiency and overall effectiveness. System level simulations have been performed using a MATLAB based LTE-A Vienna downlink simulator. RESULTS: The results show that the FFR scheduler is the best performer among the four tested algorithms. It also exhibits flexibility and adaptability for radio resource assignment. PeerJ Inc. 2021-05-18 /pmc/articles/PMC8157178/ /pubmed/34084939 http://dx.doi.org/10.7717/peerj-cs.546 Text en ©2021 Ashfaq et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Algorithms and Analysis of Algorithms
Ashfaq, Khuram
Safdar, Ghazanfar Ali
Ur-Rehman, Masood
Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
title Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
title_full Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
title_fullStr Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
title_full_unstemmed Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
title_short Comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
title_sort comparative analysis of scheduling algorithms for radio resource allocation in future communication networks
topic Algorithms and Analysis of Algorithms
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157178/
https://www.ncbi.nlm.nih.gov/pubmed/34084939
http://dx.doi.org/10.7717/peerj-cs.546
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