Currently, balancing low bitrate coding with speech quality is a highly debated topic in the research community. At very low bitrates, existing methods often fail to maintain speech naturalness, intelligibility, and personalization. To address this issue, we introduce an innovative ultra-low bitrate semantic speech coding approach, termed Semantic Speech Coding (SSC). Specifically, the multi-level feature extraction and compression mechanism sequentially extracts and compresses speech features at different levels, ensuring speech quality at ultra-low bit rates. Using a semantic vector quantization codec to fuse spectral and pitch features to extract essential semantic information, achieving more efficient compression while enhancing intelligibility and naturalness. The low-data-overhead speaker feature encoder captures time-invariant speaker characteristics, enabling personalized speech synthesis without additional data overhead, ensuring the synthesized speech retains personalization and naturalness. The diffusion loss mechanism employs a conditional diffusion model to progressively restore details, mitigating the detail loss typically seen in conventional codecs, further enhancing the naturalness and realism of the synthesized speech. We achieved significant improvements in speech quality at an ultra-low bitrate of 106 bps, which approaches the theoretical upper limit of information rate.

Affine frequency division multiplexing (AFDM) has emerged as a promising waveform for high-mobility communication systems, whose performance in doubly dispersive channels relies on accurate channel estimation. However, conventional AFDM channel estimation schemes exhibit significant limitations. Therefore, we propose a low-complexity channel estimation scheme which adopts different pilot designs for integer and fractional Doppler cases. Specifically, the generalized approximate message passing (GAMP) algorithm is employed to replace the expectation step of the sparse Bayesian learning algorithm based on expectation maximization (EM), thereby reducing computational complexity. Extensive simulation results demonstrate that, compared with conventional methods, the proposed scheme not only offers advantages in pilot power consumption and overhead, but also achieves excellent performance and low complexity in various Doppler cases.