Superimposed Pilot-Based Adaptive Semantic Communications for Wireless Image Transmission

The non-orthogonal superimposed pilot (NOSIP) scheme significantly improves the spectrum efficiency of semantic communication (SemCom) systems by effectively reducing pilot overhead. However, existing SemCom systems based on NOSIP still face challenges, including strong model-channel coupling and limited adaptability to heterogeneous channels. To address these issues, this paper proposes a flexible, channel-adaptive digital SemCom (D-SemCom) architecture based on the NOSIP scheme. Specifically, we design a lightweight semantic codec, termed ShiftViT, and a semantic receiver, termed ShiftRx, which employ time- and frequency-domain shift mechanisms to decouple pilot and data and suppress multi-user interference, thereby enabling image transmission under complex channel conditions. Furthermore, a lightweight channel adaptation algorithm based on first-order meta-learning is proposed to facilitate rapid adaptation and mitigate the strong coupling between semantic models and channel environments. Numerical results demonstrate that the proposed D-SemCom system achieves approximately 25.14% and 1.16% goodput improvements over traditional receivers and existing state-of-the-art methods, respectively, while reducing the computational complexity in terms of FLOPs by approximately 40.37%. In addition, the proposed channel adaptation algorithm is shown to rapidly adapt to diverse channel scenarios within the D-SemCom system.