University of Oulu

N. J. Mayedo Rodríguez, O. L. Alcaraz López, H. Alves and M. Latva-aho, "On the SIR Meta Distribution in Massive MTC Networks with Scheduling and Data Aggregation," 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021, pp. 1-6, doi: 10.1109/VTC2021-Spring51267.2021.9448956

On the SIR meta distribution in massive MTC networks with scheduling and data aggregation

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Author: Mayedo Rodríguez, Nelson J.1; Alcaraz López, Onel L.1; Alves, Hirley1;
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-01


Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs). The aggregators not only collect data but also implement scheduling mechanisms to cope with scarce network resources. We use the concept of meta distribution (MD) of the signal-to-interference ratio (SIR) to gain a complete understanding of the per-link reliability and describe the performance of two scheduling methods for data aggregation of machine type communication (MTC): random resource scheduling (RRS) and channel-aware resource scheduling (CRS). The results show the fraction of users in the network that achieves a target reliability, which is an important aspect to consider when designing wireless systems with stringent service requirements.

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Series: IEEE Vehicular Technology Conference
ISSN: 1090-3038
ISSN-L: 1090-3038
ISBN: 978-1-7281-8964-2
ISBN Print: 978-1-7281-8965-9
Pages: 1 - 6
Article number: 9448956
DOI: 10.1109/VTC2021-Spring51267.2021.9448956
Host publication: 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring, 25-28 April 2021, Helsinki, Finland
Conference: IEEE Vehicular Technology Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work is supported by Academy of Finland (Grants n.307492 Academy Professor, n.318927 6Genesis Flagship, n.326301 FIREMAN and no319008 EE-IoT).
Academy of Finland Grant Number: 307492
Detailed Information: 307492 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
326301 (Academy of Finland Funding decision)
319008 (Academy of Finland Funding decision)
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