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Simulation codes for estimating the probability of outage with randomly located objects and reconfigurable intelligent surfaces

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Juan Marcos Ramirez, Vincenzo Mancuso, and Marco Ajmone Marsan

22st Mediterranean Communication and Computer Networking Conference (MedComNet 2024)

Abstract

Reconfigurable intelligent surfaces (RISs) have emerged as a key technology for future communication systems. RISs are arrays of tunable reflecting elements that provide controllable propagation channels by smartly shaping incident electromagnetic (EM) waves. Analysis and improvement of RIS-aided systems require the definition of accurate path loss models that consider environmental effects often encountered in practical applications. In this paper, we derive a path loss model for RIS-assisted communications to account for the attenuation induced by the transmission medium and randomly located obstructions. More precisely, this study focuses on assessing the impact caused by Poisson-located obstructing objects on RIS-assisted millimeter wave links. To this end, we evaluate the outage probability yielded by RIS-aided systems in indoor environments with antenna beam-steering and random obstructions. We obtain extensive simulation results to assess the impact of RIS considering different parameters, such as the minimum signal-to-noise ratio (SNR) necessary for successful reception, the operating frequency, the density of the Poisson process used for object placement, and the object size.

Bibtex

@inproceedings{ramirez2024rumble,
  author={Ramírez, Juan Marcos and Mancuso, Vincenzo and Ajmone Marsan, Marco},
  booktitle={2024 22nd Mediterranean Communication and Computer Networking Conference (MedComNet)}, 
  title={The Rumble in the Millimeter Wave Jungle: Obstructions Vs Ris}, 
  year={2024},
  pages={1-10},
  doi={10.1109/MedComNet62012.2024.10578262}}

Communication System

How to run the code

The performance evaluation of RIS-assisted wireless communication systems in the presence of randomly positioned obstructions was executed interactively using Jupyter notebooks across different scenarios.

2D Indoor Case

Figure 2

  • To generate the curves in Figure 2(b), run Poutage_vs_gamma.ipynb file in the indoor2D directory. Adjust the operating frequency and the number of RIS elements to obtain different curves.

  • To generate the curves in Figure 2(c), run Poutage_vs_lambda_ppp.ipynb file in the indoor2D directory. Adjust the operating frequency and the number of RIS elements to obtain different curves.

  • To generate the curves in Figure 2(d), run Poutage_vs_radius.ipynb file in the indoor2D directory. Adjust the operating frequency and the number of RIS elements to obtain different curves.

Figure 4

  • To generate the curves in Figure 4(a), run Without_Beamsteering.ipynb file in the indoor2D directory. Adjust the operating frequency and the number of RIS elements to obtain different curves.

3D Indoor Case

Figure 5

  • To generate the curves in Figure 5, run Poutage_vs_gamma_3D.ipynb file in the indoor3D directory. Adjust the operating frequency and the number of RIS elements to obtain different curves.

Platform

The code has been executed in a Linux environment, specifically on the Ubuntu 22 Operating System.

Acknowledgments

This work has been supported by Project AEON-CPS (TSI-063000-2021-38), funded by the Ministry of Economic Affairs and Digital Transformation and the European Union NextGeneration-EU in the Spanish Recovery, Transformation, and Resilience Plan framework.

License

This code package is licensed under the GNU GENERAL PUBLIC LICENSE (version 3) - see the LICENSE file for details

Author

Juan Marcos Ramírez Rondón. Postdoctoral Researcher. IMDEA Networks Institute. Leganés, 28918, Spain.

Contact

Juan Marcos Ramirez

Date

June 16th, 2024

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Simulation codes for estimating the probability of outage with randomly located objects and reconfigurable intelligent surfaces

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