Title: Rate-Adaptive Semantic Communication via Multi-Stage Vector Quantization Show Chinese title

Title: 通过多阶段矢量量化实现速率自适应语义通信

Abstract: This paper proposes a novel framework for rate-adaptive semantic communication based on multi-stage vector quantization (VQ), termed \textit{MSVQ-SC}. Unlike conventional single-stage VQ approaches, which require exponentially larger codebooks to achieve higher fidelity, the proposed framework decomposes the quantization process into multiple stages and dynamically activates both stages and individual VQ modules. This design enables fine-grained rate adaptation under varying bit constraints while mitigating computational complexity and the codebook collapse problem. To optimize performance, we formulate a module selection problem that minimizes task loss subject to a rate constraint and solve it using an incremental allocation algorithm. Furthermore, we extend the framework by incorporating entropy coding to exploit non-uniform codeword distributions, further reducing communication overhead. Simulation results on the CIFAR-10 dataset demonstrate that the proposed framework outperforms existing digital semantic communication methods, achieving superior semantic fidelity with lower complexity while providing flexible and fine-grained rate control. Show Chinese abstract

Abstract: 本文提出了一种基于多阶段矢量量化（VQ）的速率自适应语义通信的新框架，称为\textit{MSVQ-SC}。与传统的单阶段VQ方法不同，后者需要指数级更大的码本以实现更高的保真度，所提出的框架将量化过程分解为多个阶段，并动态激活各个阶段和单独的VQ模块。这种设计在不同的比特约束下实现了细粒度的速率自适应，同时减轻了计算复杂性和码本崩溃问题。为了优化性能，我们提出了一个模块选择问题，在满足速率约束的前提下最小化任务损失，并使用增量分配算法进行求解。此外，我们通过引入熵编码扩展了该框架，以利用非均匀码字分布，进一步降低通信开销。在CIFAR-10数据集上的仿真结果表明，所提出的框架优于现有的数字语义通信方法，在实现更优语义保真度的同时具有更低的复杂度，并提供了灵活且细粒度的速率控制。