python simulator for integrated modelling of 5G (pysim5g)

Description

pysim5g is an open-source techno-economic assessment framework for 5G deployment.

Based on the Monte-Carlo method, the aim is to enable both engineering and economic cost metrics to be assessed in a unified, systematic framework.

The tool includes statistical analysis of radio interference to assess the system-level performance of 4G and 5G frequency band coexistence (including millimeter wave), while simultaneously quantifying the costs of ultra-dense 5G networks.

One example application of this framework includes exploring the techno-economics of 5G infrastructure sharing strategies.

Citation

• E. J. Oughton, K. Katsaros, F. Entezami, D. Kaleshi, and J. Crowcroft, ‘An Open-Source Techno-Economic Assessment Framework for 5G Deployment’, IEEE Access, vol. 7, pp. 155930–155940, 2019, https://doi.org/10.1109/ACCESS.2019.2949460.

Example results

Setup and configuration

All code for pysim5g is written in Python (Python>=3.5) and has a number of dependencies. See requirements.txt for a full list.

Using conda

The recommended installation method is to use conda, which handles packages and virtual environments, along with the conda-forge channel which has a host of pre-built libraries and packages.

Create a conda environment called pysim5g:

conda create --name pysim5g python=3.5

Activate it (run each time you switch projects)::

activate pysim5g

First, install required packages including fiona, shapely, numpy, rtree, pyproj and pytest:

conda install fiona shapely numpy rtree pyproj pytest

For development purposes, run this command once per machine:

python setup.py develop

To install pysim5g permanently:

python setup.py install

The run the tests:

pytest

To generate results run:

python scripts/run.py

To visualize the results, install matplotlib, pandas and seaborn:

conda install matplotlib pandas seaborn

And then run:

python vis/vis.py

Background and funding

The python simulator for integrated modelling of 5G (pysim5g) was funded by the UK Digital Catapult's ESPRC-funded Researcher in Residence programme.

Contributors

• Edward J. Oughton (University of Oxford) (Primary Investigator)
• Kostas Kotsaros (UK Digital Catapult)
• Fariborz Entezami (UK Digital Catapult)
• Dritan Kaleshi (UK Digital Catapult)
• Catarina Fernandes (UK Digital Catapult)
• Tom Russell (University of Oxford)
• Jon Crowcroft (University of Cambridge)