Deep Learning Based MIMO Signal Detection Algorithm Comparison -- 3

Job ID: 33553011

Budget: $30 – $250 USD

***In this project, in general terms, deep learning-based methods from MIMO signal detection algorithms will be compared.

***The work to be done will be carried out on Python, and MIMO signals will be generated on Matlab during the work to be done.

***In this project, BPSK, QPSK, 16QAM and 64QAM modulations on the MIMO system will be analyzed and Rayleigh channel will be used in the analysis.

***Trials will be made for different MIMO antenna configurations(2x2,4x4 etc.), and the change in performance for different situations will be shown with graphic outputs.

***The data obtained in different modulation types will be compared through the bit error rate(BER) and Signal to Noise Ratio (SNR) metric values, and the performances in different modulations will be compared with the help of the obtained data.

----------Details and must be done list:-------------

***MIMO signals will be generated using MATLAB, processed using a Python application, and turned into graphical drawings. Here, for example, the signals (numerical data) produced using MATLAB can be written to a mat or exe file, read and processed using a Python application and shown as comparative graphic drawings.

***In the process of processing the Python application, at least 1 (if possible 2) of the deep learning methods must be used. The main purpose here is to compare the data processed using normal MIMO systems and deep learning-based systems with at least 1 (if possible 2) method. During the comparison, BER and SER values will be displayed together as graphic drawings.

***Source codes are required both for codes in which MIMO signals are generated using MATLAB, and for codes that will be processed and turned into graphical illustrations using a Python application. While writing all the codes, what the code does and what source it is taken from (name, year and page of the book or article) should be stated before the relevant part as a comment line at the beginning. Which formula is used in the sections written as a comment line should also be added as a comment.

***It will be useful to include the concepts of ZF (Zero Forcing) and MMSE (minimum mean square error) in the study.

***MATLAB, Python applications, versions and tools used in the project must be written and shared as comments on the codes. In this project, in addition to the desired graphical drawings, source codes are also required. I need to be able to do my own tests and different experiments by installing the codes used in the project and related applications in my own local computer. For this reason, it is necessary to know which application to download from where and how.

***When the subject headings are searched, some shares that we come across on the internet should not be copied and pasted. In these codes, it is necessary to know which job is done on which line, and the codes should not appear when searched on the internet.

***Codes and graphical drawings should not be shared on any platform for at least 6 months after the project is completed.

***I am sharing the article of a study similar to the project to be done. Although the work done in this article does not fully meet the demands, it has been shared in terms of graphical outputs as an example of the concept.

Thanks,