Abbas, R., Al-Sherbaz, Ali ORCID: 0000-0002-0995-1262, Bennecer, A. and Piction, P. (2019) Collision Evaluation in Low Power Wide Area Networks. In: 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, pp. 1505-1512. ISBN 9781728140353
Text (Peer Reviewed Version)
9351 Abbas, R., Al-Sherbaz, A., Bennecer, A., Picton, P. (2019) Collision-evaluation-in-low-power-wide-area-networks.pdf - Accepted Version Restricted to Repository staff only Available under License All Rights Reserved. Download (1MB) |
Abstract
This paper presents a performance evaluation of intercell interference and packets collision in scalable Low Power Wide Area Networks (LPWANs). The collision problem is one of the most critical challenges in LPWANs because it can substantially affect network performance and reliability. The paper also offers a rigorous and flexible mathematical model for the ALOHA-based random access protocol with the support of multiple groups of devices and multiple message copies. The analysis is based on the worst-case scenario of message collision, which calculates the message lost ratio (MLR) by assuming that even a weak overlap between two packets in the time-frequency domain leads to the loss of both. Simulations of Weightless-N and Sigfox LPWAN technologies using a variable number of devices, message copies, payload, transmission time, and channels offer some fresh insights into the LPWANs performance. For example, increasing the number message copies reduces the MLR but only up to a certain number of connected devices. After which, the redundancy in packet transmission is no longer beneficial.
Item Type: | Book Section |
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Article Type: | Article |
Uncontrolled Keywords: | ALOHA; Collision; LPWAN; Sigfox; Weightless-N; IoT. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Schools and Research Institutes > School of Business, Computing and Social Sciences |
Research Priority Areas: | Applied Business & Technology |
Depositing User: | Kate Greenaway |
Date Deposited: | 11 Feb 2021 12:40 |
Last Modified: | 31 Aug 2023 08:01 |
URI: | https://eprints.glos.ac.uk/id/eprint/9351 |
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