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NB-IoT Random Access :
NB-IoT Random Access : Data-driven Analysis and ML-based Enhancements
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- Caso, Giuseppe (författare)
- Simula Metropolitan CDE, NOR
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- Kousias, Konstantinos (författare)
- Simula Research Laboratory, NOR
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- Alay, Özgü (författare)
- University of Oslo, NOR; Simula Metropolitan CDE, NOR
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- Brunstrom, Anna, 1967- (författare)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
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- Neri, Marco (författare)
- Rohde & Schwarz, ITA
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(creator_code:org_t)
- IEEE, 2021
- 2021
- Engelska.
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 8:14, s. 11384-11399
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In the context of massive Machine Type Communications (mMTC), the Narrowband Internet of Things (NB-IoT) technology is envisioned to efficiently and reliably deal with massive device connectivity. Hence, it relies on a tailored Random Access (RA) procedure, for which theoretical and empirical analyses are needed for a better understanding and further improvements. This paper presents the first data-driven analysis of NB-IoT RA, exploiting a large scale measurement campaign. We show how the RA procedure and performance are affected by network deployment, radio coverage, and operators’ configurations, thus complementing simulation-based investigations, mostly focused on massive connectivity aspects. Comparison with the performance requirements reveals the need for procedure enhancements. Hence, we propose a Machine Learning (ML) approach, and show that RA outcomes are predictable with good accuracy by observing radio conditions. We embed the outcome prediction in a RA enhanced scheme, and show that optimized configurations enable a power consumption reduction of at least 50%. We also make our dataset available for further exploration, toward the discovery of new insights and research perspectives.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
Nyckelord
- Cellular Internet of Things
- Downlink
- Empirical Analysis.
- Estimation
- Frequency conversion
- Internet of Things
- Long Term Evolution
- massive Machine Type Communications
- Narrowband
- Narrowband Internet of Things
- Random Access
- Synchronization
- Computer Science
- Datavetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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