Tighter bounds on the error probability of fixed convolutional codes

We introduce new upper bounds for the bit and burst error probabilities, when a convolutional code is used for transmission over a binary input, additive white Gaussian noise (AWGN) channel, and the decoder performs maximum-likelihood decoding. The bounds are tighter than existing bounds, and nontrivial also for signal-to-noise ratios below the computational cutoff rate.