This repository contains the resources and codebase for the paper titled "Energy-Efficient Massive MIMO Design: Optimal Number of Antennas Ensuring Guaranteed Bit Rate," published in the 2022 IEEE Future Networks World Forum (FNWF).
Our study explores the challenges and solutions in achieving energy efficiency in massive multi-input multi-output (mMIMO) antenna systems while ensuring a guaranteed bit rate (GBR). We introduce a novel algorithm based on symmetric game theory to optimize the energy efficiency (EE) of mMIMO systems in a multi-cell network, taking into account GBR constraints. Additionally, we propose a data traffic model that aligns various user equipment capabilities and mobile data applications with corresponding GBR levels.
- Algorithm Development: Developed an algorithm using the symmetric-game best response strategy to balance the GBR requirements with the highest possible energy efficiency in mMIMO designs.
- Data Traffic Model: Introduced a model that translates user bit rate requirements into GBR levels, considering a range of user equipment capabilities and applications.
- Simulation Results: Provided simulation results demonstrating the effectiveness of the proposed algorithm in achieving GBR requirements with minimal deviation from optimal EE targets.
Instructions on how to set up the environment, run simulations, and interpret results.
- To re-draw the figures, please execute the
generateFigures.m - To re-produce the simulation results, please execute
Run_Simulation_OptimumEE_BS_GDR.m
If you use the resources from this repository, please cite:
@INPROCEEDINGS{abuibaid2022mmimo,
author={Abuibaid, Mohammed and St-Hilaire, Marc and Aldirmaz-Colak, Sultan and Eid, Imad},
booktitle={2022 IEEE Future Networks World Forum (FNWF)},
title={Energy-Efficient Massive MIMO Design: Optimal Number of Antennas Ensuring Guaranteed Bit Rate},
year={2022},
pages={328-333},
doi={10.1109/FNWF55208.2022.00064}
}