Automatic Modulation Classification for OFDM Signals Based On Modified K-Means Clustering Algorithm
Publish place: Third National Conference and First International Conference on Applied Research in Electrical, Mechanical and Mechatronics Engineering
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ELEMECHCONF03_0059
تاریخ نمایه سازی: 9 مرداد 1395
Abstract:
Automatic Modulation Classification (AMC) has attracted many researchers’ attention in different civilian and military purposes. This paper presents a novel modulation classification algorithm based on modified K-means cluster analysis. Generally, we aim to distinguish OFDM signals from single-carrier modulations. In this regard, two statistics of the amplitude of received signal are calculated as key features. The extracted features of training data points are submitted to the clustering algorithm and centers for single-carrier and multicarrier modulations are assessed. Afterwards, each point of testing dataset is dedicated to its nearest center based on Euclidian distance and the classification is accomplished. The simulation results demonstrate that the algorithm is beneficial in a wide range from low to high SNRs.
Keywords:
Classification Algorithms , Automatic Modulation Classification (AMC) , Orthogonal Frequency-Division Multiplexing (OFDM) , multicarrier (MC) modulations , single-carrier (SC) modulations
Authors
S. Norouzi
Electrical and Computer Engineering School, Communications and Electronics Department Shiraz University Shiraz, Iran
A. Jamshidi
Electrical and Computer Engineering School, Communications and Electronics Department Shiraz University Shiraz, Iran
A.R Zolghadrasli
Electrical and Computer Engineering School, Communications and Electronics Department Shiraz University Shiraz, Iran
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