Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/65566
Title: | Efficient papr regulation in OFDM system using soft computing techniques |
Researcher: | Patidar,Manish Kumar |
Guide(s): | Pachauri, Rahul, Mishra, Amit and Saxena, Rajiv |
Keywords: | Artificial Neural Network OFDM PAPR Soft Computing |
University: | Jaypee University of Engineering and Technology, Guna |
Completed Date: | 30/11/2015 |
Abstract: | Multi-Carrier Modulation technique have gained popularity in recent years among other modulation techniques The special form of MCM viz Orthogonal Frequency Division Multiplexing attracted vast attention of people like academician researchers and industrialist due to its capability of high data rate transmission The various communication standards like Wireless Local Area Network Worldwide Interoperability for Microwave Access Fourth Generation 4G mobile communication Digital Audio Broadcasting and Digital Video Broadcasting are used OFDM technique for signal transmission newlineThe basic idea of the OFDM technique is to divide the entire frequency channel into many narrowband subcarriers which are orthogonal to each other These subcarriers have a potential to transmit information at a high bit rate and to reduce Inter Symbol Interference substantially On the contrary one of the major drawbacks of OFDM technique is high Peak to Average Power Ratio The PAPR affects the efficiency of Digital to Analog Converter introduces nonlinearity in High Power Amplifier increases spectral spreading and allows Bit Error Rate degradation newlineSoft computing is a consortium of methodologies that works synergistically and provides flexible information processing capability for handling real life ambiguous situations The important members of soft computing family are Artificial Neural Network Fuzzy logic Genetic algorithm and Adaptive Network Based Fuzzy Inference System Nowadays these techniques are being used in various applications in the field of communication engineering such as channel equalization estimation of parameters of nonlinear systems pattern recognition and reduction of computational complexity of the system newline newline |
Pagination: | xiv,119p. |
URI: | http://hdl.handle.net/10603/65566 |
Appears in Departments: | Department of Electronics and Communication |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 31.64 kB | Adobe PDF | View/Open |
02_certificate.pdf | 31.69 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 20.77 kB | Adobe PDF | View/Open | |
04_declaration.pdf | 19.14 kB | Adobe PDF | View/Open | |
05_acknowledgement.pdf | 21.08 kB | Adobe PDF | View/Open | |
06_content.pdf | 60.17 kB | Adobe PDF | View/Open | |
07_list_of_tables.pdf | 19.25 kB | Adobe PDF | View/Open | |
08_list_of_figures.pdf | 40.04 kB | Adobe PDF | View/Open | |
09_list of abbrivations_and_symbol.pdf | 115.51 kB | Adobe PDF | View/Open | |
10_chapter_1.pdf | 165.69 kB | Adobe PDF | View/Open | |
11_chapter_2.pdf | 1.05 MB | Adobe PDF | View/Open | |
12_chapter_3.pdf | 964.12 kB | Adobe PDF | View/Open | |
13_chapter_4.pdf | 414.58 kB | Adobe PDF | View/Open | |
14_chapter_5.pdf | 566 kB | Adobe PDF | View/Open | |
15_chapter_6.pdf | 607.9 kB | Adobe PDF | View/Open | |
16_chapter_7.pdf | 51.56 kB | Adobe PDF | View/Open | |
17_ conclusion .pdf | 75.11 kB | Adobe PDF | View/Open | |
18_biblography.pdf | 186.74 kB | Adobe PDF | View/Open | |
19_list_of_publication.pdf | 21.39 kB | Adobe PDF | View/Open |
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