Noise immunity performance analysis based on MATLAB various amplitude modulation methods

Shuao Yang; Juzheng Zhang; Yang Zhang

doi:10.1117/12.2655491

7 October 2022 Noise immunity performance analysis based on MATLAB various amplitude modulation methods

Shuao Yang, Juzheng Zhang, Yang Zhang

Proceedings Volume 12344, International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022); 123440J (2022) https://doi.org/10.1117/12.2655491
Event: International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022), 2022, Zhuhai, China

Abstract

Analog modulation is one of the hot topics in current research. Digital technology cannot completely replace analog technology, and analog modulation is the basic method of communication. Researchers have found and proved that the anti-noise capability of the receiver can measure the reliability of the system, but there is still a gap in the research on the anti-noise performance of different modulation modes. Based on MATLAB, this study analyzes the influence of different modulation methods on the anti-noise performance by using program design and analyzes the anti-noise performance of each modulation method by contrast analysis and control variables, and compares the performance of each modulation method. Through the experiment of this study, it is found that the modulation regime gain G of different amplitude modulation modes is different, so each mode has different anti-noise performance. These different modulation modes have advantages and disadvantages, so in practical application, it is necessary to choose the appropriate modulation mode according to the demand.

Citation Download Citation

Shuao Yang, Juzheng Zhang, and Yang Zhang "Noise immunity performance analysis based on MATLAB various amplitude modulation methods", Proc. SPIE 12344, International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022), 123440J (7 October 2022); https://doi.org/10.1117/12.2655491

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