CUMULANT APPROACH FOR MODULATION RECOGNITION
Keywords:
SIGNAL MODEL, MQAM SIGNAL PROPERTIESAbstract
In this paper, cumulant approach is used in MQAM modulated signal recognition. This method uses the characteristics of higher-order cumulants and higher-order statistics to identify different kinds of MQAM signals. We focus on the modulation identification using statistical properties of MQAM signals. The reason of using this method is the ability of higher-order statistics to reflect the distribution characteristics of the constellation diagram.Thereare many benefits of using this method. This method needs only small amount of computations. It can effectively inhibit the effects of White Gaussian Noise. In many applications,the cumulants are applicable to distinguish between different amplitude or phase modulated signals like MQAM, MPSK,MASK. Differentmodulated signals have different cumulant values. Whenever we use higher order cumulants, we will get higher degree to distinguish the type of modulation scheme; the higher order cumulants require a large amount of data. A good characteristic of this method is that: the value of higher order cumulants (more than two orders), for the Gaussian noise is zero, so the use of higher-order cumulants characteristics can effectively remove the impact of the Gaussian noise.Simulation results reflectthe validity of proposed algorithm.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Under the Creative Commons Attribution- 4.0 International License (CC BY-4.0 DEED).
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
