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.
@article{arxiv.2101.05333,
title = {On the SIR Meta Distribution in Massive MTCNetworks with Scheduling and Data Aggregation},
author = {Nelson J. Mayedo Rodríguez and Onel L. Alcaraz López and Hirley Alves and Matti Latva-aho},
journal= {arXiv preprint arXiv:2101.05333},
year = {2021}
}
Comments
The manuscript has 6 pages and 5 figures. The paper is accepted at IEEE VTC Spring 2021