Cambridge Digital Communications Assessment Model
Cambridge Digital Communications Assessment Model (cdcam)
The Cambridge Digital Communications Assessment Model (
cdcam) is a decision support tool
to quantify the performance of national digital infrastructure strategies for mobile broadband,
focussing on 4G and 5G technologies.
- Oughton, E.J. and Frias, Z. (2017) The Cost, Coverage and Rollout Implications of 5G Infrastructure in Britain. Telecommunications Policy. https://doi.org/10.1016/j.telpol.2017.07.009.
- Oughton, E.J., Z. Frias, T. Russell, D. Sicker, and D.D. Cleevely. 2018. Towards 5G: Scenario-Based Assessment of the Future Supply and Demand for Mobile Telecommunications Infrastructure. Technological Forecasting and Social Change, 133 (August): 141–55. https://doi.org/10.1016/j.techfore.2018.03.016.
- Oughton, E.J., Frias, Z., van der Gaast, S. and van der Berg, R. (2019) Assessing the Capacity, Coverage and Cost of 5G Infrastructure Strategies: Analysis of The Netherlands. Telematics and Informatics (January). https://doi.org/10.1016/j.tele.2019.01.003.
Setup and configuration
All code for The Cambridge Digital Communications Assessment Model is written in Python (Python>=3.5). The core model has no other dependencies.
requirements-dev.txt for a full list of optional dependencies used in supporting
Create a conda environment called
conda create --name cdcam python=3.7
Activate it (run this each time you switch projects):
conda activate cdcam
First, install optional packages:
conda install fiona shapely rtree pyproj tqdm
pip install cdcam
Alternatively, for development purposes, clone this repository and run:
python setup.py develop
Install test/dev requirements:
conda install pytest pytest-cov
Run the tests:
pytest --cov-report=term --cov=cdcam tests/
If you want to quickly generate results, first download the sample dataset available at DOI 10.5281/zenodo.3525285, then run:
You should see the model printing output such as
Running: baseline baseline macrocell
which means the data have been loaded and you are running the baseline population scenario,
baseline data throughput scenario and macrocell upgrade strategy.
You should then see an output for each year (
- 2020) indicating how much money was spent on
either servicing a specified coverage obligation (
Service) or in meeting demand (
- 2020 Service 0 Demand 14614 - 2021 Service 0 Demand 3293
More details are provided in the Getting Started documentation.
Contributions to this package are welcomed via the usual pull request mechanism.
If you encounter a bug, feel the documentation is incorrect or incomplete, or want to suggest new features, please post an issue in the issues tab.
Background and funding
The Cambridge Digital Communications Assessment Model has been collaboratively developed between the Environmental Change Institute at the University of Oxford, the Networks and Operating Systems Group (NetOS) at the Cambridge Computer Laboratory, and the UK's Digital Catapult. Research activity between 2017-2018 also took place at the Cambridge Judge Business School at the University of Cambridge.
- Edward J. Oughton (University of Oxford)
- Tom Russell (University of Oxford)
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