The performance of a low complexity decision aided turbo equalization using NSC and RSC codes

In this paper a low complexity adaptive Turbo equalization scheme using classical nonsystematic and recently proposed recursive systematic convolutional codes (NSC and RSC) has been analyzed. Although it was shown that at low signal to noise ratio (SNR), RSC outperforms the best NSC codes, in terms...

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Bibliographische Detailangaben
Hauptverfasser:	Trajkovic, V.D., Rapajic, P.B.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adaptive equalizers AWGN Bit error rate Communication channels Convolution Convolutional codes Decision feedback equalizers Finite impulse response filter Maximum likelihood estimation Signal to noise ratio
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Beschreibung
Zusammenfassung:	In this paper a low complexity adaptive Turbo equalization scheme using classical nonsystematic and recently proposed recursive systematic convolutional codes (NSC and RSC) has been analyzed. Although it was shown that at low signal to noise ratio (SNR), RSC outperforms the best NSC codes, in terms of bit error rate (BER), it is not the case when both codes are used in the proposed adaptive Turbo scheme. The results have been confirmed by simulations when the communication is performed over different communication channels and different code constraint lengths.
DOI:	10.1109/TELSKS.2003.1246262