Cellular Network Capacity Planning for Future Smart-Grid Services
Možný, Radek (2025)
Omakustanne/Self-published
2025
Tieto- ja sähkötekniikan tohtoriohjelma - Doctoral Programme in Computing and Electrical Engineering
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Väitöspäivä
2025-05-27
Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-03-3923-4
https://urn.fi/URN:ISBN:978-952-03-3923-4
Kuvaus
Cotutelle -yhteisväitöskirja
Tiivistelmä
The increasing demands of smart-grid applications in the landscape of Industrial Internet of Things (IIoT) require optimized communication networks, particularly through Narrowband IoT (NB-IoT) and Long Term Evolution for Machine-Type Communication (LTE-M or eMTC). This dissertation provides novel strategies to enhance these technologies to meet the critical requirements of reliability, low latency, and efficient traffic management, including permanent connectivity in smart-grid deployments driven by regulatory entities, such as the European Parliament and its directives.
A core component of this research is an comprehensive measurement campaign conducted to assess the performance of NB-IoT and eMTC in both controlled environments and realistic smart-grid conditions with heavy traffic loads. The results reveal that while NB-IoT offers superior coverage, it struggles to meet the high-throughput and low-latency demands of smart-grid networks. These findings highlight the need for optimized message distribution on single or a Multi-Radio Access Technology (Multi-RAT) approach to optimize performance by leveraging both NB-IoT and eMTC.
To address the specific challenges posed by smart-grid deployment, several models have been introduced to assess the stability and delay performance of NB-IoT networks based on the gathered results. The generalized Markov chain model highlights the limitations of the NB-IoT in supporting End Devices (EDs) with permanent connectivity, leading to significant delays under high traffic loads, even for 100 EDs. By increasing radio resources in the first model and optimizing message transmission intervals in the simplified model, this research improves the delay performance and balances the network load more effectively, enabling the coexistence of densely deployed traditional sensors and several hundred permanently connected smart meters. Additionally, techniques such as Early Data Transmission (EDT) have been explored, demonstrating substantial latency reductions of more than 50% and enhanced efficiency for smaller message sizes. These optimizations demonstrated efficacy in meeting the smart-grid latency requirements.
Furthermore, an optimal RAT association algorithm is proposed to manage the communication load between the NB-IoT and eMTC EDs to increase communication reliability. This approach ensures more efficient operations by dynamically balancing traffic across technologies, leading to a reduction in latency and an increase in system reliability compared to single-RAT deployments. The algorithm successfully meets the strict latency requirements of smart-grid systems, enabling reliable communication even under diverse geographical conditions and varying deployment densities reaching up to 3,000 EDs.
A core component of this research is an comprehensive measurement campaign conducted to assess the performance of NB-IoT and eMTC in both controlled environments and realistic smart-grid conditions with heavy traffic loads. The results reveal that while NB-IoT offers superior coverage, it struggles to meet the high-throughput and low-latency demands of smart-grid networks. These findings highlight the need for optimized message distribution on single or a Multi-Radio Access Technology (Multi-RAT) approach to optimize performance by leveraging both NB-IoT and eMTC.
To address the specific challenges posed by smart-grid deployment, several models have been introduced to assess the stability and delay performance of NB-IoT networks based on the gathered results. The generalized Markov chain model highlights the limitations of the NB-IoT in supporting End Devices (EDs) with permanent connectivity, leading to significant delays under high traffic loads, even for 100 EDs. By increasing radio resources in the first model and optimizing message transmission intervals in the simplified model, this research improves the delay performance and balances the network load more effectively, enabling the coexistence of densely deployed traditional sensors and several hundred permanently connected smart meters. Additionally, techniques such as Early Data Transmission (EDT) have been explored, demonstrating substantial latency reductions of more than 50% and enhanced efficiency for smaller message sizes. These optimizations demonstrated efficacy in meeting the smart-grid latency requirements.
Furthermore, an optimal RAT association algorithm is proposed to manage the communication load between the NB-IoT and eMTC EDs to increase communication reliability. This approach ensures more efficient operations by dynamically balancing traffic across technologies, leading to a reduction in latency and an increase in system reliability compared to single-RAT deployments. The algorithm successfully meets the strict latency requirements of smart-grid systems, enabling reliable communication even under diverse geographical conditions and varying deployment densities reaching up to 3,000 EDs.
Kokoelmat
- Väitöskirjat [5020]