Semantic-Importance-Aware Reordering-Enhanced Semantic Communication System With OFDM Transmission

As a novel communication paradigm, semantic communication (SemCom) can greatly improve communication efficiency, which has aroused extensive research by scholars worldwide. As one of the important aspects of digital communication nowadays, how to combine channel estimation with SemCom is an important research direction. In this article, based on orthogonal frequency-division multiplexing (OFDM) communication architecture, the semantic importance-aware reordering-enhanced SemCom system (SIARE-SC) is proposed, which utilizes the inequality of semantic symbols combined with channel estimation in OFDM systems to reduce the distortion caused by channel estimation interpolation error (CEIE) and further improve the signal recovery quality. To enhance the generalizability of the system, we extend the verification of the effectiveness of SIARE-SC in various scenarios with different sources, channels, and pilot patterns. Furthermore, the importance reordering method proposed in the SIARE-SC has good applicability and effectiveness, which can be used to be compatible with other SemCom systems and has a significant suppression effect on the peak-to-average power ratio (PAPR). Meanwhile, CEIE has been considered for the first time to be included in the analysis of SemCom distortion, and mathematically derive the performance expressions of SIARE-SC under different channel and pilot pattern scenarios from three perspectives, namely, channel bandwidth ratio (CBR), signal-to-noise ratio (SNR), and CEIE, to obtain the corresponding bound of performance. The proposed SIARE-SC is shown to significantly improve semantic performance in various scenarios by conducting a large number of experimental tests.