Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/8811
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dc.contributor.authorMahera, Mrunalini-
dc.date.accessioned2019-08-30T09:41:59Z-
dc.date.available2019-08-30T09:41:59Z-
dc.date.issued2018-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/8811-
dc.description.abstractAutomatic Modulation Classification has been an important theme with the develop- ment of wireless communications.It is widely applied to the uncooperative communication field for military or civilian purpose.Automatic Modulation Classification is a middle step between signal interception and information recovery.Modulation recognition is extremely important in Signal monitoring system.The classification of the communication system done by inspecting the received signal properties like modulation type,carrier frequency and so on. Generally any automatic modulation classification system which is based up on de- cision -theoretic approach,in which there are three stages:1)pre- processing, 2)extraction of key feature and 3) Modulation classification of signal. Firstly out of six key features extract only one key feature and it is max which is spectral power density of instantaneous amplitude extracted from intercepted signal us- ing MATLAB code simulation. Next extract key feature max from intercepted signals with different modulation in- dex and vary the SNR from 10 to 20 dB.Then decide the threshold value of key features and compare them with their threshold and after that decide modulation type of unknown signals.Here,the modulation types which are discriminate here includes AM,FM,ASK,BPSK and QPSK. Thereafter,frequency estimation from the noisy signal spectrum by MUSIC(Multiple Signal Classification) algorithm which used Eigen-based subspace decomposition method. Then frequencies of multiple incident signals can be estimated by spectral peak searching using MATLAB code simulation.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries16MECC10;-
dc.subjectEC 2016en_US
dc.subjectProject Reporten_US
dc.subjectProject Report 2016en_US
dc.subjectEC Project Reporten_US
dc.subjectEC (Communication)en_US
dc.subjectCommunicationen_US
dc.subjectCommunication 2016en_US
dc.subject16MECCen_US
dc.subject16MECC10en_US
dc.titleDesign and Implementation of Automatic Modulation Classification Algorithmsen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, EC (Communication)

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