发表机构
ZGC Institute of Ubiquitous-X Innovation and Applications; Beijing Key Laboratory of 6G DOICT converged and Cloud-Native Mobile Information Networks; State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications（ZGC通用X创新与应用研究所; 北京6G DOICT融合与云原生移动信息网络重点实验室; 北京邮电大学网络与交换技术国家重点实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对高分辨率遥感图像传输中极限压缩与鲁棒性的矛盾，提出DVQ-SDSC框架，通过双分支非对称编解码和PCA辅助G-DPCM索引压缩，在AFDM信道上以0.0625 BPP超越JPEG-LDPC。
AI 中文摘要
高分辨率遥感图像（RSI）传输受限于星地带宽和信道损伤，然而现有方法难以同时实现极限压缩和鲁棒传输。为解决此问题，我们提出了一种双分支矢量量化辅助的卫星数字语义通信（DVQ-SDSC）框架，用于在仿射频分复用（AFDM）上传输RSI，其带宽节省源于两个相互关联的方面。首先，在信源编码层面，开发了一个双分支框架，以端到端架构统一深度联合语义编码、矢量量化辅助索引传输、信道估计与自适应；不同于对称编码器设计，编解码器被重构为非对称双分支架构，分别处理高频残差和低频结构语义，通过门控融合和信道自适应重建共同恢复语义内容。其次，在索引编码层面，我们开发了主成分分析（PCA）辅助的码本重排，使索引拓扑与潜在相关性对齐，并设计了组差分脉冲编码调制（G-DPCM）来编码预测残差而非绝对索引，从而降低索引比特率，同时局部隔离削波和信道错误。两阶段训练策略进一步将信道损伤与语义编解码器解耦。在3GPP NTN-TDL-D信道上的FAIR1M实验表明，采用G-DPCM索引编码的DVQ-SDSC在0.0625比特每像素（BPP）的基础速率下优于传统JPEG-LDPC方案，且G-DPCM可直接应用于已训练的编解码器而无需重新训练，以零额外成本实现额外的索引压缩。
英文摘要
High-resolution remote sensing imagery (RSI) transmission is constrained by satellite-ground bandwidth and channel impairments, yet existing methods struggle to simultaneously achieve extreme compression and robust transmission. To address this, we propose a dual-branch vector-quantization aided satellite digital semantic communication (DVQ-SDSC) framework for RSI transmission over affine frequency division multiplexing (AFDM), whose bandwidth savings arise from two interrelated aspects. First, at the source-coding level, a dual-branch framework is developed to unify deep joint semantic coding, VQ-aided index transmission, channel estimation and adaption in an end-to-end architecture; departing from symmetric encoder designs, the codec is recast as an asymmetric dual-branch architecture that separately processes the high-frequency residuals and the low-frequency structural semantics, with gated fusion and channel-adaptive reconstruction jointly restoring the semantic content. Second, at the index-coding level, we develop a principal component analysis (PCA)-aided codebook reordering to align index topology with latent correlations, and devise group differential pulse-code modulation (G-DPCM) to encode prediction residuals rather than absolute indices, lowering the index bitrate while locally isolating clipping and channel errors. A two-stage training strategy further decouples channel impairments from the semantic codec. FAIR1M experiments over 3GPP NTN-TDL-D demonstrate that DVQ-SDSC with G-DPCM index coding outperforms the conventional JPEG-LDPC scheme at the base rate of 0.0625 bits per pixel (BPP), and that G-DPCM applies directly to the trained codec without retraining, yielding additional index compression at no extra cost.
