The application of large-scale MIMO detection algorithm in 5G and beyond 5G

Qiteng Tang

doi:10.1117/12.3027113

1 April 2024 The application of large-scale MIMO detection algorithm in 5G and beyond 5G

Qiteng Tang

Proceedings Volume 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024); 1307706 (2024) https://doi.org/10.1117/12.3027113
Event: 4th International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 2024, Chicago, IL, United States

Abstract

In recent years, the rapid advancement of 5G technology has brought to the forefront the pivotal role of Multiple-Input Multiple-Output (MIMO) system algorithms. This paper delves into a comprehensive exploration of two distinct algorithmic approaches within the context of 5G applications for massive MIMO systems. These two approaches are matrix transformation and machine learning, and the following paragraphs will shed light on their respective attributes and intricacies. Matrix transformation is a fundamental technique in MIMO systems, which aims to optimize the transmission of signals by manipulating the channel matrices. This method, while established and reliable, exhibits certain limitations in accommodating the dynamic and complex nature of 5G environments. On the other hand, machine learning algorithms, with their adaptability and capacity for self-improvement, have gained prominence in recent years. They offer a promising avenue for addressing the challenges presented by 5G MIMO systems, such as handling interference and optimizing resource allocation. In this paper, we provide concrete examples to analyze the strengths and weaknesses of both matrix transformation and machine learning in the context of 5G applications. Furthermore, we explore potential directions for the application of these algorithms and propose areas for improvement, with the ultimate goal of enhancing the efficiency and performance of massive MIMO systems in the evolving landscape of 5G technology.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiteng Tang "The application of large-scale MIMO detection algorithm in 5G and beyond 5G", Proc. SPIE 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 1307706 (1 April 2024); https://doi.org/10.1117/12.3027113

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Multiple input multiple output

Detection and tracking algorithms

Machine learning

Matrices

Data modeling

Error analysis

Signal detection

Show All Keywords

Keywords/Phrases

Search In:

Publication Years