Automatic Modulation Classification using Principle Composition Analysis based Features Selection
Objective
The primary aim is to design a robust and efficient algorithm capable of accurately classifying modulations in communication signals by leveraging PCA-derived features.
Abstract
Automatic Modulation Classification (AMC) plays an important role in both military and civilian applications. Feature based AMC is used in this paper. Principle Component Analysis (PCA) is employed to reduce dimensions of the feature vector. Two classifiers mainly k-nearest neighbour (KNN) and Support Vector Machine (SVM) are used to investigate the correct classification rate against different SNRs for test signals. Experiments are conducted using data trained at two different SNRs of 15dB and 3dB respectively. Results show that KNN classifier shows better results when data is trained at high SNRs. However, both the classifiers show almost same performance when data is trained at low SNR.
Keywords: Automatic Modulation Classification; Principle Component Analysis; Feature based; classifier; Support Vector Machine; k-Nearest Neighbour
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Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
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RAM:
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Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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