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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) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2021100149101 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2021
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| Publish Date: | 2021-10-01 |
| Description: |
AbstractData 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. see all
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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 |
| OADOI: | https://oadoi.org/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 |
| Subjects: | |
| 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 318927 326301 319008 |
| 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) |
| Copyright information: |
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |