Convolutional decoding in the presence of false alarms
We propose a new channel model that is suited for systems with irregular sampling, e.g. selective data embedding in digital media. The channel model accounts for the possible occurrence of false alarms, i.e. extra data bits, in the received sequence. We propose modifications to the common decoding schemes of the convolutional codes namely, the Viterbi and the sequential decoding to compensate for these false alarms. The simulation results establish the effectiveness of the proposed algorithms in detecting false alarms with high rates.