title: A novel modulation classification approach using Gabor filter network.
abstract: A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel.
authors.affiliation: ISRA University, Islamabad 44000, Pakistan ; School of Engineering & Applied Sciences (SEAS), ISRA University, Islamabad Campus, I/10 Markaz, Islamabad 44000, Pakistan ; International Islamic University, Islamabad 44000, Pakistan.
authors.forename: Sajjad Ahmed
authors.initials: SA
authors.lastname: Ghauri
authors.affiliation: AIR University, Islamabad 44000, Pakistan ; Institute of Signals, Systems and Soft Computing (ISSS), Islamabad, Pakistan.
authors.forename: Ijaz Mansoor
authors.initials: IM
authors.lastname: Qureshi
authors.affiliation: ISRA University, Islamabad 44000, Pakistan ; Institute of Signals, Systems and Soft Computing (ISSS), Islamabad, Pakistan.
authors.forename: Tanveer Ahmed
authors.initials: TA
authors.lastname: Cheema
authors.affiliation: International Islamic University, Islamabad 44000, Pakistan ; Institute of Signals, Systems and Soft Computing (ISSS), Islamabad, Pakistan.
authors.forename: Aqdas Naveed
authors.initials: AN
authors.lastname: Malik
mesh_terms: D003142:Communication; D016013:Likelihood Functions; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D012984:Software; D013997:Time Factors