Access and Backhaul Solutions for Cellular-Enabled Industrial Wearables
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Authors
Saafi, Salwa
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Referee
Mark
P
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Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Abstract
Smartphones are no longer the only portable devices changing the lives and daily routines of today’s digitally connected consumers. Smart glasses, watches, headsets, cameras, bands, trackers, monitors, and scanners are all examples of hands-free inherently mobile wearable devices that enable the emerging consumer and industrial applications. Similarly to customers who are ready to embrace life-changing experiences with new devices, companies and industries are also employing smart helpers and intelligent assistant systems to improve the efficiency of their automated processes and the productivity and safety of their workers. Not limited to the employment of smart helpers, the industrial digital transformation relies heavily on the deployment of communication infrastructures that utilize efficient cellular technologies to meet the dissimilar requirements of industrial applications. Motivated by these intelligent assistant systems and communication technologies, this dissertation focuses on the role of wearable technology and cellular connectivity in enabling the automation of vertical domains. Aiming to address the current technology gap behind cellular-enabled industrial wearables, the present work is dedicated to assessing the applicability of cellular connectivity to industrial wearables and developing efficient access and backhaul solutions for the support of the requirements of emerging industrial applications. The following outline of this dissertation is built around the main objectives as highlighted above and presents the main outcomes of this work, which include (i) a concise technology review capturing the evolution of the recent solutions proposed by the 3rd Generation Partnership Project (3GPP) for wearable devices and communications, (ii) an introduction to novel categories of industrial wearable applications with mid-end requirements that fall in-between the two extremes of high-end and low-end Fifth-Generation (5G) service classes, (iii) an assessment of the applicability of the emerging Reduced-Capability New Radio (NR RedCap) technology to the newly introduced wearable applications, (iv) an extension of the RedCap wearable communications with Device-to-Device (D2D) and Supplementary Uplink (SUL) capabilities for enhanced access network performance, (v) a cost-efficient backhaul selection solution based on Markov Decision Processes (MDPs) for time-sensitive wearable applications in an integrated terrestrial and non-terrestrial communication scenario, and (vi) a data-driven Artificial Intelligence (AI)-aided approach for the management of complex industrial networks with dissimilar device capabilities, communication solutions, and application requirements. A set of simulation and analytical models is developed to assess the relevant key performance indicators as part of the above contributions. Beyond indicating the need for technology improvement demanded by the efficient integration of wearable devices into cellular networks and the satisfaction of industrial application requirements, the numerical results reported in this dissertation confirm the network performance enhancements achieved by the access and backhaul solutions contributed in this work.
Smartphones are no longer the only portable devices changing the lives and daily routines of today’s digitally connected consumers. Smart glasses, watches, headsets, cameras, bands, trackers, monitors, and scanners are all examples of hands-free inherently mobile wearable devices that enable the emerging consumer and industrial applications. Similarly to customers who are ready to embrace life-changing experiences with new devices, companies and industries are also employing smart helpers and intelligent assistant systems to improve the efficiency of their automated processes and the productivity and safety of their workers. Not limited to the employment of smart helpers, the industrial digital transformation relies heavily on the deployment of communication infrastructures that utilize efficient cellular technologies to meet the dissimilar requirements of industrial applications. Motivated by these intelligent assistant systems and communication technologies, this dissertation focuses on the role of wearable technology and cellular connectivity in enabling the automation of vertical domains. Aiming to address the current technology gap behind cellular-enabled industrial wearables, the present work is dedicated to assessing the applicability of cellular connectivity to industrial wearables and developing efficient access and backhaul solutions for the support of the requirements of emerging industrial applications. The following outline of this dissertation is built around the main objectives as highlighted above and presents the main outcomes of this work, which include (i) a concise technology review capturing the evolution of the recent solutions proposed by the 3rd Generation Partnership Project (3GPP) for wearable devices and communications, (ii) an introduction to novel categories of industrial wearable applications with mid-end requirements that fall in-between the two extremes of high-end and low-end Fifth-Generation (5G) service classes, (iii) an assessment of the applicability of the emerging Reduced-Capability New Radio (NR RedCap) technology to the newly introduced wearable applications, (iv) an extension of the RedCap wearable communications with Device-to-Device (D2D) and Supplementary Uplink (SUL) capabilities for enhanced access network performance, (v) a cost-efficient backhaul selection solution based on Markov Decision Processes (MDPs) for time-sensitive wearable applications in an integrated terrestrial and non-terrestrial communication scenario, and (vi) a data-driven Artificial Intelligence (AI)-aided approach for the management of complex industrial networks with dissimilar device capabilities, communication solutions, and application requirements. A set of simulation and analytical models is developed to assess the relevant key performance indicators as part of the above contributions. Beyond indicating the need for technology improvement demanded by the efficient integration of wearable devices into cellular networks and the satisfaction of industrial application requirements, the numerical results reported in this dissertation confirm the network performance enhancements achieved by the access and backhaul solutions contributed in this work.
Smartphones are no longer the only portable devices changing the lives and daily routines of today’s digitally connected consumers. Smart glasses, watches, headsets, cameras, bands, trackers, monitors, and scanners are all examples of hands-free inherently mobile wearable devices that enable the emerging consumer and industrial applications. Similarly to customers who are ready to embrace life-changing experiences with new devices, companies and industries are also employing smart helpers and intelligent assistant systems to improve the efficiency of their automated processes and the productivity and safety of their workers. Not limited to the employment of smart helpers, the industrial digital transformation relies heavily on the deployment of communication infrastructures that utilize efficient cellular technologies to meet the dissimilar requirements of industrial applications. Motivated by these intelligent assistant systems and communication technologies, this dissertation focuses on the role of wearable technology and cellular connectivity in enabling the automation of vertical domains. Aiming to address the current technology gap behind cellular-enabled industrial wearables, the present work is dedicated to assessing the applicability of cellular connectivity to industrial wearables and developing efficient access and backhaul solutions for the support of the requirements of emerging industrial applications. The following outline of this dissertation is built around the main objectives as highlighted above and presents the main outcomes of this work, which include (i) a concise technology review capturing the evolution of the recent solutions proposed by the 3rd Generation Partnership Project (3GPP) for wearable devices and communications, (ii) an introduction to novel categories of industrial wearable applications with mid-end requirements that fall in-between the two extremes of high-end and low-end Fifth-Generation (5G) service classes, (iii) an assessment of the applicability of the emerging Reduced-Capability New Radio (NR RedCap) technology to the newly introduced wearable applications, (iv) an extension of the RedCap wearable communications with Device-to-Device (D2D) and Supplementary Uplink (SUL) capabilities for enhanced access network performance, (v) a cost-efficient backhaul selection solution based on Markov Decision Processes (MDPs) for time-sensitive wearable applications in an integrated terrestrial and non-terrestrial communication scenario, and (vi) a data-driven Artificial Intelligence (AI)-aided approach for the management of complex industrial networks with dissimilar device capabilities, communication solutions, and application requirements. A set of simulation and analytical models is developed to assess the relevant key performance indicators as part of the above contributions. Beyond indicating the need for technology improvement demanded by the efficient integration of wearable devices into cellular networks and the satisfaction of industrial application requirements, the numerical results reported in this dissertation confirm the network performance enhancements achieved by the access and backhaul solutions contributed in this work.
Description
Citation
SAAFI, S. Access and Backhaul Solutions for Cellular-Enabled Industrial Wearables [online]. Brno: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. 2023.
Document type
Document version
Date of access to the full text
Language of document
en
Study field
bez specializace
Comittee
prof. Ing. Jaroslav Koton, Ph.D. (předseda)
Prof. Frank H. P. Fitzek (Opponent) (člen)
Prof. Antti Tölli (Pre-examiner) (člen)
Assoc. Prof. Zdenek Becvar (Pre-examiner) (člen)
prof. Ing. Zdeněk Smékal, CSc. (člen)
Ing. Pavel Mašek, Ph.D. (člen)
Prof. Elena - Simona Lohan (člen)
Assoc. Prof. Jiri Hosek (Supervisor) (člen)
Assoc. Prof. Sergey Andreev (Supervisor) (člen)
Dr. Olga Vikhrova (Co-supervisor) (člen)
Date of acceptance
2023-05-17
Defence
Obhajoba práce probíhala hybridní formou v prostředí MS teams. Setkání zahájil předseda prof. Koton, kdy uvítal uchazečku, členy komise a přítomné hosty. Slovo bylo předáno Ms. Saafi, která v rámci svého vystoupení prezentoval motivaci, dosažené výsledky a perspektivy další vědeckovýzkumné činnosti v oblasti tématu disertace. Následovala otevřená diskuze, především mezi Ms. Saafi a prof. prof. Fitzek, do které se zapojili i ostatní členové komise (prof. Tölli, doc. Bečvář). V detailu byly diskutovány hlavní přínosy disertační práce, které byly rozděleny do tří skupin. Pozornost byla také věnována možnostem budoucího aplikačního využití v praxi. Byly položeny i otázky související s budoucím vývojem a možnostem využití umělé inteligence. Ms. Saafi na dotazy reagovala pohotově a prokázala svoji erudici v oboru. Kromě členů komise se veřejné části zúčastnilo také 14 hostů. Celková doba veřejného vystoupení trvala přes 1,5 hodiny. Následovalo uzavřené jednání členů komise, která tajně hlasovala.
The dissertation defense took place hybrid using MS Teams tool. The event was initiated by the committee chair prof. Koton, who welcomed the applicant, the committee members, and guests. Ms. Saafi was asked to give her presentation, who within her speech discussed the motivation, reached results and perspectives for further research in the area of the dissertation topic. The presentation followed by open discussion, primarily between Ms. Saafi and prof. Fitzek, whereas also other committee members raised their questions (prof. Tölli, assoc. prof. Bečvář). The main contribution of the dissertation, divided in three main domains, was discussed in detail. The attention was also paid to future application of the results in practice. Questions to future challenges and possible utilization of artificial intelligence were raised. Ms. Saafi always responded promptly and proved her erudition in the area. Next to the committee members, 14 guests were also present during the public part. The public part of the defense took over 1.5 hour. It was followed by non-public meeting of the committee members and secrete vote.
Result of defence
práce byla úspěšně obhájena
Document licence
Standardní licenční smlouva - přístup k plnému textu bez omezení