Abstract
Massive Machine-Type Communications (mMTC) are one of the three types of services that should be supported by 5G networks. These are distinguished by the need to serve a large number of devices which are characterized by non-intensive traffic and low energy consumption. While the sporadic nature of the mMTC traffic does not pose an exertion to efficient network operation, multiplexing the traffic from a large number of these devices within the cell certainly does. Therefore, planning carefully the network resources for this traffic is of paramount importance. To do this, the statistics of the traffic pattern that arrives at the base station should be known. To this end, in this paper, we derive the distribution of the inter-arrival times of the traffic at the base station from a general number of mMTC users within the cell, assuming a generic distribution of the traffic pattern by individual users. We validate our results on traces. Results show that adding more mMTC users in the cell increases the variability of the traffic pattern at the base station almost linearly, which is not the case with increasing the traffic generation rates.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 652-660 |
| Number of pages | 9 |
| Journal | Proceedings - IEEE Consumer Communications and Networking Conference, CCNC |
| DOIs | |
| State | Published - 2022 |
| Event | 19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022 - Virtual, Online, United States Duration: Jan 8 2022 → Jan 11 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Artificial Intelligence
- Electrical and Electronic Engineering
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