The BCJR algorithm, named after its developers Bahl, Cocke, Jelinek, and Raviv, is a soft-decision decoding technique used for error correction in convolutional codes. This algorithm uses a forward-backward approach to calculate the posterior probabilities of the state transitions and symbols, providing a powerful method to improve decoding performance. It plays a significant role in soft-decision decoding by leveraging the received signals' likelihood to enhance the accuracy of the decoded information, which is essential in applications involving noisy communication channels.
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