Cargando…
A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks
To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or tr...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506608/ https://www.ncbi.nlm.nih.gov/pubmed/32877983 http://dx.doi.org/10.3390/s20174907 |
_version_ | 1783585052907536384 |
---|---|
author | Ssajjabbi Muwonge, Bernard Pei, Tingrui Sansa Otim, Julianne Mayambala, Fred |
author_facet | Ssajjabbi Muwonge, Bernard Pei, Tingrui Sansa Otim, Julianne Mayambala, Fred |
author_sort | Ssajjabbi Muwonge, Bernard |
collection | PubMed |
description | To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or transmission delay alone, the complexity is aggravated by the simultaneous consideration of all these three variables jointly in addition to a channel selection variable, since it creates a non-convex problem. Our objective is to jointly optimize the three major variables; transmission power, rate and delay under constraints of Bit Error Rate (BER), interference and other channel limitations. We analyze how total power, rate and delay vary with packet size, network size, BER and interference. The resulting problem is solved using a branch-and-cut polyhedral approach. For simulation of results, we use MATLAB together with the state-of-the-art BARON software. It is observed that an increase in packet size generally leads to an increase in total rate, total power and total transmission delay. It is also observed that increasing the number of secondary users on the channel generally leads to an increased power, delay and rate. |
format | Online Article Text |
id | pubmed-7506608 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75066082020-09-26 A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks Ssajjabbi Muwonge, Bernard Pei, Tingrui Sansa Otim, Julianne Mayambala, Fred Sensors (Basel) Article To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or transmission delay alone, the complexity is aggravated by the simultaneous consideration of all these three variables jointly in addition to a channel selection variable, since it creates a non-convex problem. Our objective is to jointly optimize the three major variables; transmission power, rate and delay under constraints of Bit Error Rate (BER), interference and other channel limitations. We analyze how total power, rate and delay vary with packet size, network size, BER and interference. The resulting problem is solved using a branch-and-cut polyhedral approach. For simulation of results, we use MATLAB together with the state-of-the-art BARON software. It is observed that an increase in packet size generally leads to an increase in total rate, total power and total transmission delay. It is also observed that increasing the number of secondary users on the channel generally leads to an increased power, delay and rate. MDPI 2020-08-31 /pmc/articles/PMC7506608/ /pubmed/32877983 http://dx.doi.org/10.3390/s20174907 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ssajjabbi Muwonge, Bernard Pei, Tingrui Sansa Otim, Julianne Mayambala, Fred A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks |
title | A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks |
title_full | A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks |
title_fullStr | A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks |
title_full_unstemmed | A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks |
title_short | A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks |
title_sort | joint power, delay and rate optimization model for secondary users in cognitive radio sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506608/ https://www.ncbi.nlm.nih.gov/pubmed/32877983 http://dx.doi.org/10.3390/s20174907 |
work_keys_str_mv | AT ssajjabbimuwongebernard ajointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT peitingrui ajointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT sansaotimjulianne ajointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT mayambalafred ajointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT ssajjabbimuwongebernard jointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT peitingrui jointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT sansaotimjulianne jointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks AT mayambalafred jointpowerdelayandrateoptimizationmodelforsecondaryusersincognitiveradiosensornetworks |