Performance Bounds for Convolutional Codes with Digital Viterbi Decoders in Gaussian Noise

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With digital implementations of the Viterbi decoding algorithm for convolutional codes, soft quantization is preferred over hard quantization because it generally yields superior performance. Since the decoder needs to know the signal energy and channel noise variance with soft quantization, inaccurate information can result in a mismatch between the channel and decoder. Bounds which are tight for high signal-to-noise ratios are obtained on the bit error probability using the generating function approach. Automatic gain control level inaccuracies, imperfect carrier phase, symbol timing synchronization error, and path metric digitization are discussed in the context of a mismatch between the channel and decoder.