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L. Stobbe et al.
increase. It is currently unknown in which areas (inner city, suburban, rural area)
network densification will take place to what extent. It can be assumed that the cell
density will not be expanded to the same extent in all areas. Another factor driving
for higher absolute energy and material consumption is the increased demand for
broadband transport networks (optical fiber or directional radio). Furthermore, the
coordination of the higher number of small cells requires additional computation
power.
The research question in this context is; what is the absolute demand for energy
and materials due to the expansion of densified networks and to what extent is
this potential increase compensated by the improved (relative) energy and material
efficiency.
15.6 Discussion of Scientific Challenges
There are a couple of challenges related to this approach. First of all, a considerable
technical understanding of existing and future technologies is necessary to create a
realistic channel model as the model comes close to simulating real networks. At
least in the first stages, a very high level of detail is required to understand which
elements have a significant impact. It is expected that only after one or two exemplary
calculations it is possible to correct the proportions of the model.
The largest challenge is the acquisition of detailed technical data. Obtaining data
for existing mobile networks is less of a problem, as market statistics and product data
sheets can be used in this context. This is far more difficult for future technologies and
networks. Good sources of information are standardization documents and research
reports. Still, concrete data such as device configuration options, exact localization of
network components, power consumption values, load profiles and bills of materials
are not yet available.
To compensate for the lack of information, physical, electrical, and thermodynamic models are considered to be a viable option for estimating the physical dimensions and power usage of future equipment. These can include the following: characteristic curves for power supplies, signal propagation models, heat management
calculations, load profiles, models to estimate the computational effort for signal
processing, etc.
The effort and expertise needed to reliably predict and plan the design and functionality of products that do not yet exist is challenging, but a rough estimate to
assess the order of magnitude that can be checked against current technical data and
roadmap recommendations is reasonably sufficient for modelling the impact.
Since small errors can lead to large deviations when the model is scaled from,
for example, a small region to a national level, plausibility checks and iterative
corrections are obligatory.
L. Stobbe et al.
increase. It is currently unknown in which areas (inner city, suburban, rural area)
network densification will take place to what extent. It can be assumed that the cell
density will not be expanded to the same extent in all areas. Another factor driving
for higher absolute energy and material consumption is the increased demand for
broadband transport networks (optical fiber or directional radio). Furthermore, the
coordination of the higher number of small cells requires additional computation
power.
The research question in this context is; what is the absolute demand for energy
and materials due to the expansion of densified networks and to what extent is
this potential increase compensated by the improved (relative) energy and material
efficiency.
15.6 Discussion of Scientific Challenges
There are a couple of challenges related to this approach. First of all, a considerable
technical understanding of existing and future technologies is necessary to create a
realistic channel model as the model comes close to simulating real networks. At
least in the first stages, a very high level of detail is required to understand which
elements have a significant impact. It is expected that only after one or two exemplary
calculations it is possible to correct the proportions of the model.
The largest challenge is the acquisition of detailed technical data. Obtaining data
for existing mobile networks is less of a problem, as market statistics and product data
sheets can be used in this context. This is far more difficult for future technologies and
networks. Good sources of information are standardization documents and research
reports. Still, concrete data such as device configuration options, exact localization of
network components, power consumption values, load profiles and bills of materials
are not yet available.
To compensate for the lack of information, physical, electrical, and thermodynamic models are considered to be a viable option for estimating the physical dimensions and power usage of future equipment. These can include the following: characteristic curves for power supplies, signal propagation models, heat management
calculations, load profiles, models to estimate the computational effort for signal
processing, etc.
The effort and expertise needed to reliably predict and plan the design and functionality of products that do not yet exist is challenging, but a rough estimate to
assess the order of magnitude that can be checked against current technical data and
roadmap recommendations is reasonably sufficient for modelling the impact.
Since small errors can lead to large deviations when the model is scaled from,
for example, a small region to a national level, plausibility checks and iterative
corrections are obligatory.