AI 中文总结
研究提出空间语义通信（SSC）系统，利用流体天线 - 索引调制（FA - IM）技术，结合剩余量化（RQ）方法与语义感知流分割方案，有效整合多种优势，为数字语义传输提供稳健解决方案。
AI 中文摘要
当前数字语义通信系统主要致力于与传统星座调制保持兼容。相比之下，索引调制（IM）通过利用额外维度进行信息传输，是一种频谱和能量效率更高的选择。本文认识到这一潜力，通过提出一种利用前沿流体天线 - 索引调制（FA - IM）技术的新型空间语义通信（SSC）系统，弥合了IM与语义通信之间的差距。该系统与现有联合信源信道编码（JSCC）架构兼容，采用剩余量化（RQ）方法离散化模拟语义特征以进行后续数字IM传输。特别地，通过语义感知流分割方案协同RQ和IM，确保关键语义信息受信道衰落影响较小，进一步优化语义传输性能。仿真结果验证了该系统有效整合了RQ的高保真度、语义感知分割的可靠性和FA - IM的空间效率，为未来数字语义传输提供了稳健解决方案。
英文摘要
Current digital semantic communication systems have primarily focused on maintaining compatibility with conventional constellation-based modulation. In contrast, index modulation (IM) represents a more spectrally and energy-efficient alternative by exploiting additional dimensions for information conveyance. Recognizing this potential, this paper bridges the gap between IM and semantic communications by proposing a novel spatial semantic communication (SSC) system leveraging cutting-edge fluid antenna-IM (FA-IM) technology. Compatible with existing joint source-channel coding (JSCC) architectures, the proposed SSC system employs the residual quantization (RQ) approach to discretize analog semantic features for subsequent digital IM transmission. Notably, the proposed SSC system synergizes RQ and IM via a semantic-aware stream splitting scheme, which ensures that critical semantic information undergoes less severe channel fading, thereby further optimizing semantic transmission performance. Simulation results validate that the proposed SSC system effectively integrates the high fidelity of RQ, the reliability of semantic-aware splitting, and the spatial efficiency of FA-IM, thereby providing a robust solution for future digital semantic transmission. The open source code is available at: https://github.com/gxh1106/SSC.
CommentsAccepted by IEEE TCOM
