Linear Code

Linear codes are fundamental structures in information theory, aiming to efficiently and reliably transmit data across noisy channels. Current research emphasizes developing improved decoding algorithms, particularly using deep learning architectures like Transformers and graph neural networks, to enhance performance and flexibility across various code types (e.g., LDPC, BCH, Polar codes) and channel conditions. This work is driven by the need for robust and adaptable error correction in applications like 6G wireless communication and secure communication systems, with a focus on optimizing code design for short block lengths and efficient hardware implementation.