A re-think is required on the role of small-cells to help build green, sustainable networks.
Small-Cells
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By deploying the “right” number of smaller base-stations, instead of a single large base station, significant energy savings can be realised, without compromising on network coverage and capacity, as per a new research.The ability to reduce the required deployment height of small base-stations to as low as 15m reduces Opex and faster TTM. Furthermore, the reduction in transmit power of smartphones leads to an increase in the battery life by about ~50%.
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It’s true that small cells have had very limited deployments because of practical issues and the impression that overall energy consumption may end up on the higher side if there too many small cells.
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This new research is worth your consideration and to build upon.
New Research
Today, we have a conjunction of open source tools available, such as Sionna ray-tracing digital-twin framework that can integrate with Blender + OSM, and they allow creating a digital copy of a physical scene and model the wireless environment accurately and predict signal coverage by simulating EM phenomenon like diffraction, scattering and multipath.
The ray-tracing framework brings explicit knowledge of the environment to help figure out the “right” number of small base-stations needed and placing them strategically, so as to reduce overall network energy consumption.
By testing multiple locations in the ray-tracing scene, one can directly determine the overlaps, missing areas and optimize the locations.
- An NP-Hard Problem
But, to test for each and every location to determine the best locations in a brute force manner blows up the complexity and it becomes an np-hard problem.
Instead, researchers used a sub-sampling approach which exploits continuous nature of wireless channel and break the entire scene into discrete grids and then computes small-cell coverage at each of these points.
Then, by utilizing the greedy algorithm, they were able to efficiently compute the “right” number of low-power low-coverage base-stations, as well as their respective locations. See the paper for mathematical intricacies behind the greedy algorithm design.
Some Limitations
A rigorous analysis is needed by also considering the energy consumption of enlarged backhaul network and then more precisely quantify the energy savings at network level.
Sionna is able to map the wireless channel path loss really well for distances < 500m. However, for farther distances (>1 km), the generated rays by sionna become sparser and the framework predicts inconsistent results.
(CC - Emeka Obiodu, PhD, NVIDIA)
Indoor, Elevation not considered etc.
References
Densified, smaller base-stations can conquer the increasing carbon footprint problem in nextG wireless [2403.13611] Densify & Conquer: Densified, smaller base-stations can conquer the increasing carbon footprint problem in nextG wireless
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