Zero-Shot Knowledge Base Resizing for Rate-Adaptive Digital Semantic Communication
Shumin Yao, Hui Du, Lifeng Xie, Yaping Sun, Hao Chen, Nan Ma, and Xiaodong Xu

TL;DR
This paper introduces a zero-shot method for dynamically resizing the knowledge base in VQ-VAE-based semantic communication systems, enabling flexible rate adaptation without retraining and maintaining high reconstruction quality.
Contribution
We propose a novel hierarchical KB resizing approach using hyperbolic embedding and semantic tree construction, allowing instant rate adaptation without retraining.
Findings
Achieves near-scratch quality with minimal computational cost
Enables flexible, on-the-fly rate adaptation in semantic communication
Demonstrates robustness at very low rates, preventing catastrophic failure
Abstract
Digital semantic communication systems, which often leverage the Vector Quantized Variational Autoencoder (VQ-VAE) framework, are pivotal for future wireless networks. In a VQ-VAE-based semantic communication system, the transmission rate is directly governed by the size of a discrete codebook known as knowledge base (KB). However, the KB size is a fixed hyperparameter, meaning that adapting the rate requires training and storing a separate model for each desired size -- a practice that is too computationally and storage-prohibitive to achieve truly granular rate control. To address this, we introduce a principled, zero-shot KB resizing method that enables on-the-fly rate adaptation without any retraining. Our approach establishes a global importance ranking for all vectors within a single, large parent KB by uncovering its inherent semantic hierarchy. This is achieved via a three-step…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Signal Modulation Classification · Advanced Data Compression Techniques · Wireless Communication Security Techniques
