Automatic Modulation Classification Using Combination of Genetic Programming and KNN

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Aslam:2012:ieeeTWC,

• author = "Muhammad Waqar Aslam and Zhechen Zhu and Asoke Kumar Nandi",
• title = "Automatic Modulation Classification Using Combination of Genetic Programming and {KNN}",
• journal = "IEEE Transactions on Wireless Communications",
• year = "2012",
• volume = "11",
• number = "8",
• pages = "2742--2750",
• month = aug,
• keywords = "genetic algorithms, genetic programming, Automatic modulation classification, K-nearest neighbour, Classification using genetic programming, Higher order cumulants",
• ISSN = "1536-1276",
• DOI = "doi:10.1109/TWC.2012.060412.110460",
• size = "9 pages",
• abstract = "Automatic Modulation Classification (AMC) is an intermediate step between signal detection and demodulation. It is a very important process for a receiver that has no, or limited, knowledge of received signals. It is important for many areas such as spectrum management, interference identification and for various other civilian and military applications. This paper explores the use of Genetic Programming (GP) in combination with K-nearest neighbour (KNN) for AMC. KNN has been used to evaluate fitness of GP individuals during the training phase. Additionally, in the testing phase, KNN has been used for deducing the classification performance of the best individual produced by GP. Four modulation types are considered here: BPSK, QPSK, QAM16 and QAM64. Cumulants have been used as input features for GP. The classification process has been divided into two-stages for improving the classification accuracy. Simulation results demonstrate that the proposed method provides better classification performance compared to other recent methods.",
• notes = "Also known as \cite{6213036}",

}

Genetic Programming entries for Muhammad Waqar Aslam Zhechen Zhu Asoke K Nandi

Citations