Group Throughput Optimization in Wireless Communications via Spatial Beamforming

Author: Sun Haoxin, Xu Zewei and Wu Yujie

Introduction

This is a repo for EPFL COM-500 (Statistical Signal and Data Processing through Applications) mini-project: Beamforming for Throughput Optimization in 5G.

In this project, we use two different ways to do beamforming for a MISO downlink communication system: matched beamforming and flexibeam. More detailed description can be found in our report.

Project Structure

- data
  - data_1.mat         % DOA estimation results of dataset 1
  - data_2.mat         % DOA estimation results of dataset 2
  - original_data     % real signal received by a base station
    - data_1.npz      % dataset 1
    - data_2.npz      % dataset 2
    - README.txt
- MATLAB              % matlab source code
  - flexibeam.m       % flexibeam
  - matched_beamforming.m   % matched beamforming
- python-Notebook     % python notebook source code
  - doa.ipynb         % DOA estimation
  - flexibeam.ipynb   % flexibeam
  - matched_beam.ipynb  % matched beamforming
  - MVDR_beam.ipynb   % MVDR beamforming
  - Simulation.ipynb  % simulation with flexibeam and matched beamforming
- report.pdf          % our report for these two methods

References

1. P. Hurley and M. Simeoni, "Flexibeam: Analytic spatial filtering by beamforming," 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, pp. 2877-2880, doi: 10.1109/ICASSP.2016.7472203.
2. Simeoni, Matthieu & Hurley, Paul. (2016). Beamforming towards regions of interest for multi-site mobile networks.
3. Krim, H., & Viberg, M. (1996). Two decades of array signal processing research: the parametric approach. IEEE signal processing magazine, 13(4), 67-94.