🤖 AI Summary
This work addresses the limitation of conventional communication systems, which provide uniform protection for all messages and thus fail to meet the heterogeneous reliability requirements of semantic-aware applications. Focusing on short block-length communication scenarios, the paper proposes a message-level non-uniform error protection coding scheme that directly embeds message importance levels into the Hamming distance structure of the codebook. By assigning larger intra-group minimum distances to higher-importance message groups and optimizing inter-group distance constraints, the method achieves differentiated error-correction capability without requiring explicit protection labels. Experimental results over both AWGN and VLC-ISI channels demonstrate significant improvements over label-based ECC baselines in terms of bit error rate performance and classification accuracy of importance-based message grouping.
📝 Abstract
Conventional communication systems are mainly designed to reduce error rates and increase transmission rates, and therefore usually provide uniform protection to all transmitted messages. However, in intent-oriented applications, different messages may have different semantic meanings and importance levels, requiring different levels of reliability. This paper proposes a layered construction of message-level unequal error protection (UEP) codes for short-blocklength communication. Instead of appending an explicit protection tag to each codeword, the proposed method embeds the protection structure directly into the Hamming-distance structure of the codebook. By assigning larger minimum intra-level distances to higher-importance message groups and imposing suitable inter-level distance constraints, the proposed codebook provides differentiated error-correction capabilities while enabling reliable importance-level classification at the receiver. Theoretical conditions for correct group classification are derived, and simulations over AWGN and VLC-ISI channels show that the proposed scheme improves BER performance and group classification accuracy compared with a tag-based ECC baseline.