Abstract
We study in this paper optimal control strategy for Advanced Sleep Modes (ASM) in 5G networks. ASM correspond to different levels of sleep modes ranging from deactivation of some components of the base station for several micro-seconds to switching off of almost all of them for one second or more. ASMs are made possible in 5G networks thanks to the definition of so-called lean carrier radio access which allows for configurable signaling periodicities. We model such a system using Markov Decision Processes (MDP) and find optimal sleep policy in terms of a trade-off between saved power consumption versus additional incurred delay for user traffic which has to wait for the network components to be woken-up and serve it. Eventually, for the system not to oscillate between sleep levels, we add a switching component in the cost function and show its impact on the energy reduction versus delay trade-off.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE 18th International Symposium on Network Computing and Applications, NCA 2019 |
| Editors | Aris Gkoulalas-Divanis, Mirco Marchetti, Dimiter R. Avresky |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728125220 |
| DOIs | |
| Publication status | Published - 1 Sept 2019 |
| Event | 18th IEEE International Symposium on Network Computing and Applications, NCA 2019 - Cambridge, United States Duration: 26 Sept 2019 → 28 Sept 2019 |
Publication series
| Name | 2019 IEEE 18th International Symposium on Network Computing and Applications, NCA 2019 |
|---|
Conference
| Conference | 18th IEEE International Symposium on Network Computing and Applications, NCA 2019 |
|---|---|
| Country/Territory | United States |
| City | Cambridge |
| Period | 26/09/19 → 28/09/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- 5G networks
- Advanced Sleep Modes
- Delay
- Dynamic Programming
- Energy consumption
- Markov Decision Process
- Optimal policy
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