Performance Prediction of a Turbo-coded Link in Fading Channels

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Määttänen, Helka-Liina Anis, Muhammad Moiz 2012-03-12T07:06:54Z 2012-03-12T07:06:54Z 2010
dc.description.abstract Channel coding is the method of adding redundancy to the data in order to reduce the frequency of errors or to increase the capacity of a channel. Turbo codes are the most superior class of codes making achievable channel capacity almost at par with the Shannon limits. In Adaptive Modulation and Coding (AMC) the prediction of error performance of a channel is an important step before choosing one of the Modulation Coding Scheme (MCS). Since in Turbo-coded system we donot have analytical relations to relate error performance with the Signal to Noise Ratio (SNR). Therefore, normally simulation results are stored in the form of the look up tables. In this work we propose an error performance prediction model for a BPSK modulated Turbo-coded link. This model predicts performance addressing the fading phenomena for wireless radio channels. It takes the large variations in the SNR level within a code block into account along with the coding parameters. The SNR dB values profile inside a code block is considered in terms of their mean and variance. The model proposed is UMTS compliant and is continuous for values of the MCS code rate and the mean and variance of SNR dB values. It is an easier way of predicting link level performance as it replaces the discrete look up tables. Unlike the look-up tables it can be used for differentiation based analytical techniques used in system level optimization. en
dc.format.extent 78
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto University en
dc.publisher Aalto-yliopisto fi
dc.title Performance Prediction of a Turbo-coded Link in Fading Channels en
dc.type G2 Pro gradu, diplomityö fi Elektroniikan, tietoliikenteen ja automaation tiedekunta fi
dc.subject.keyword Fading en
dc.subject.keyword BLER en
dc.subject.keyword effective SNR en
dc.subject.keyword mean en
dc.subject.keyword variance en
dc.subject.keyword Turbo-codes en
dc.identifier.urn URN:NBN:fi:aalto-201203131482
dc.type.dcmitype text en
dc.programme.major Tietoliikennetekniikka fi
dc.programme.mcode S-72
dc.type.ontasot Diplomityö fi
dc.type.ontasot Master's thesis en
dc.contributor.supervisor Tirkkonen, Olav
dc.location P1 fi

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