Channel Decoder

Channel decoding aims to recover transmitted information corrupted by noise during communication. Current research emphasizes improving decoding efficiency and reliability, focusing on adaptive decoding schemes that adjust to varying channel conditions and energy constraints, as well as novel architectures like deep-unfolded iterative detection and decoding and graph neural networks that offer improved performance and reduced complexity compared to traditional methods. These advancements are crucial for enhancing the performance of wireless communication systems, particularly in resource-limited environments and applications demanding low latency, such as federated learning and 6G networks.