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Inhaltsangabe
A new adaptive filter is proposed for the turbo decoding on Rayleigh fading channels with noisy channel estimates. In this book, by using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5X10^4. Based on this research, it would be more interesting for further researchers to develop an adaptive filter that uses the extrinsic information of both systematic bits and parity bits.
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Reseña del editor
A new adaptive filter is proposed for the turbo decoding on Rayleigh fading channels with noisy channel estimates. In this book, by using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5X10^4. Based on this research, it would be more interesting for further researchers to develop an adaptive filter that uses the extrinsic information of both systematic bits and parity bits.
Biografía del autor
YuQing Guo, M.A.Sc: Studied Electrical and Computer Engineering at University of Windsor. Controls Specialist at Con-Syst-Int Group Inc., Windsor, Ontario
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Adaptive Channel Estimation for Turbo Decoding
Verlag:
LAP Lambert Academic Publishing Mai 2014, 2014
ISBN 10: 365954342X
ISBN 13: 9783659543425
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Taschenbuch
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Taschenbuch. Zustand: Neu. Neuware -A new adaptive filter is proposed for the turbo decoding on Rayleigh fading channels with noisy channel estimates. In this book, by using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5X10^4. Based on this research, it would be more interesting for further researchers to develop an adaptive filter that uses the extrinsic information of both systematic bits and parity bits.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Artikel-Nr. 9783659543425
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