Abstract: We propose a maximum a posteriori (MAP)-approaching decoder, namely a posteriori guessing random additive noise decoding (AP-GRAND), which generalizes the existing maximum likelihood ...
Abstract: In this letter, we propose a low-complexity universal decoder for product codes based on guessing codeword decoding (GCD). Recognizing that errors typically concentrate at the intersections ...
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