Best rate 1/2 convolutional codes for turbo equalization with severe ISI

摘要

We give a procedure to find good convolutional codes for use with iterative decoding (turbo equalization) of the coded AWGN intersymbol interference (ISI) channel. The method is based on the input-output bit error rate characteristic of the convolutional BCJR module in the iterative decoder, in combination with the code minimum distance. Both are essential to find best codes. Best feedforward and recursive systematic codes are listed for memories 2–4, and some individual good codes at memory 5. Codes are tested over a root raised-cosine faster than Nyquist channel with severe ISI. Turbo BER performance reaches 0.8–1.6 dB from capacity with a 4–16 state codes. Feedforward codes perform better than recursive systematic.