16-QAM-Detection-MIMO

DEPENDENCIES

Python 3.7.5

Numpy 1.17.2

matplotlib 3.1.1

CVXPY 1.0.25

INSTALLATION

Easiest way is to create a new Anaconda environment and install all necessary dependencies. If prefer not using Anaconda, just install all dependencies using plain pip, the Package Installer for Python.

ANACONDA

conda create -n mimo python=3.7 matplotlib numpy cvxpy

conda activate mimo

MOSEK SOLVER

Solver used for optimization is MOSEK. In order to use it, you will need to request a mosek trial license and follow the steps indicated there.

FILES

mimo.py - Looping through all SNRs specified for obtaining symbol errors using SDR and simple quantization, eigenvalue decomposition and randomization approximation techniques.

plot.py - Calculate Symbol error rates from mimo.py output log file and plot them.

optimization.py - Optimization module, it performs the SDR, minimizing the trace(W*A)

utils.py - Diverse utils necessary to perform the MIMO detection.

detection.py - Principal detection module.

remove_comments.py - Script to remove comments from files.

report.pdf - Slides explaining the work realized in this repository. Used for class presentation.

REMOVE COMMENTS

As the repository being a mere illustration of MIMO detection, it is full of comments to help grasp all the information.

In order to remove comments from files, just run the script remove_comments.py. By default is set to remove comments from detection.py, creating a new file called detection_no_comments.py.

To delete comments from other files, just change the last line of remove_comments.py:

remove_comments('detection.py', 'detection_no_comments.py')

Change detection.py to the file you want to remove comments (specify path if is outside of root directory)
Change detection_no_comments.py to your output-No-comments-file that will be generated.

TODO

Add code license
Add support for Maximum likelihood, zeroforcing and other detectors to compare results with SDR.
Create an object Detector to choose between different detectors implemented.

REFERENCES

[1] Semidefinite Relaxation for Detection of 16-QAM Signaling in MIMO Channels -- -- A. Wiesel ; Y.C. Eldar ; S. Shamai

[2] MOSEK

[3] CVXPY

[4] Mathworks - Compute BER for a QAM system with AWGN

[5] Google Colab

betegon / 16-QAM-Detection-MIMO