Intelligent interleaver for PAPR reduction
In orthogonal frequency division multiplexing (OFDM) systems, one of the major problems to be tackled is high peak to average power ratio (PAPR). In this paper a PAPR reduction scheme for OFDM system is proposed that takes the advantage of the classification capability of learning vector quantizatio...
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creator | Khalid, S. Zaka, I. Tasneem, K.T. Shah, S.I. Ahmed, J. |
description | In orthogonal frequency division multiplexing (OFDM) systems, one of the major problems to be tackled is high peak to average power ratio (PAPR). In this paper a PAPR reduction scheme for OFDM system is proposed that takes the advantage of the classification capability of learning vector quantization (LVQ) networks. The symbols are distributed in different classes and interleaved by a different interleaver, to achieve minimum PAPR before they are transmitted. A tremendous reduction in number of computations is achieved to get the required reduction in PAPR values. |
doi_str_mv | 10.1109/ICEE.2008.4553923 |
format | Conference Proceeding |
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In this paper a PAPR reduction scheme for OFDM system is proposed that takes the advantage of the classification capability of learning vector quantization (LVQ) networks. The symbols are distributed in different classes and interleaved by a different interleaver, to achieve minimum PAPR before they are transmitted. 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A tremendous reduction in number of computations is achieved to get the required reduction in PAPR values.</description><subject>Binary phase shift keying</subject><subject>Computer architecture</subject><subject>Fading</subject><subject>Learning vector quantization</subject><subject>Neurons</subject><subject>OFDM</subject><subject>Orthogonal frequency division multiplexing</subject><subject>Peak to average power ratio</subject><subject>Peak to average ratio</subject><subject>Power engineering and energy</subject><subject>Prototypes</subject><subject>Robustness</subject><subject>Vector quantization</subject><isbn>9781424422920</isbn><isbn>1424422922</isbn><isbn>9781424422937</isbn><isbn>1424422930</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVj0FLxDAUhCOyoK79AeKlZ6H15b2kaY5LqVpYcJG9L0n6ViK1K2kV_PeuuBdPM8M3DIwQNxJKKcHed03blghQl0prskhnIrOmlgqVQrRkzv9lhIW4-q1bQEnyQmTT9AYA0lSKQF2Ku26ceRjiK49zHo8-Dey-OOX7Q8o3q81Lnrj_DHM8jNdisXfDxNlJl2L70G6bp2L9_Ng1q3URLcyFNkC-D0ZTrRFDb2xgDUECIWhLXFF_xJK990G5GhV6rbR3wVSGK65pKW7_ZiMz7z5SfHfpe3d6Sz_ziESe</recordid><startdate>200803</startdate><enddate>200803</enddate><creator>Khalid, S.</creator><creator>Zaka, I.</creator><creator>Tasneem, K.T.</creator><creator>Shah, S.I.</creator><creator>Ahmed, J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200803</creationdate><title>Intelligent interleaver for PAPR reduction</title><author>Khalid, S. ; Zaka, I. ; Tasneem, K.T. ; Shah, S.I. ; Ahmed, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-5703bdc7538522cd79ce50c10320593e63dbdc1ebbbc4a8242b545bac767e6e83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Binary phase shift keying</topic><topic>Computer architecture</topic><topic>Fading</topic><topic>Learning vector quantization</topic><topic>Neurons</topic><topic>OFDM</topic><topic>Orthogonal frequency division multiplexing</topic><topic>Peak to average power ratio</topic><topic>Peak to average ratio</topic><topic>Power engineering and energy</topic><topic>Prototypes</topic><topic>Robustness</topic><topic>Vector quantization</topic><toplevel>online_resources</toplevel><creatorcontrib>Khalid, S.</creatorcontrib><creatorcontrib>Zaka, I.</creatorcontrib><creatorcontrib>Tasneem, K.T.</creatorcontrib><creatorcontrib>Shah, S.I.</creatorcontrib><creatorcontrib>Ahmed, J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Khalid, S.</au><au>Zaka, I.</au><au>Tasneem, K.T.</au><au>Shah, S.I.</au><au>Ahmed, J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Intelligent interleaver for PAPR reduction</atitle><btitle>2008 Second International Conference on Electrical Engineering</btitle><stitle>ICEE</stitle><date>2008-03</date><risdate>2008</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><isbn>9781424422920</isbn><isbn>1424422922</isbn><eisbn>9781424422937</eisbn><eisbn>1424422930</eisbn><abstract>In orthogonal frequency division multiplexing (OFDM) systems, one of the major problems to be tackled is high peak to average power ratio (PAPR). In this paper a PAPR reduction scheme for OFDM system is proposed that takes the advantage of the classification capability of learning vector quantization (LVQ) networks. The symbols are distributed in different classes and interleaved by a different interleaver, to achieve minimum PAPR before they are transmitted. A tremendous reduction in number of computations is achieved to get the required reduction in PAPR values.</abstract><pub>IEEE</pub><doi>10.1109/ICEE.2008.4553923</doi><tpages>4</tpages></addata></record> |
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subjects | Binary phase shift keying Computer architecture Fading Learning vector quantization Neurons OFDM Orthogonal frequency division multiplexing Peak to average power ratio Peak to average ratio Power engineering and energy Prototypes Robustness Vector quantization |
title | Intelligent interleaver for PAPR reduction |
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