Task-oriented semantic communications (TSC) enhance radio resource efficiency by transmitting task-relevant semantic information. However, current research often overlooks the inherent semantic distinctions among encoded features. Due to unavoidable channel variations from time and frequency-selective fading, semantically sensitive feature units could be more susceptible to erroneous inference if corrupted by dynamic channels. Therefore, this letter introduces a unified channel-resilient TSC framework via information bottleneck. This framework complements existing TSC approaches by controlling information flow to capture fine-grained feature-level semantic robustness. Experiments on a case study for real-time subchannel allocation validate the framework's effectiveness.

翻译：面向任务语义通信通过传输任务相关的语义信息增强无线资源效率。然而，现有研究常忽略编码特征中固有的语义差异。由于时频选择性衰落导致的信道变化难以避免，若遭受动态信道损害，语义敏感特征单元更易产生错误推理。为此，本文提出一种基于信息瓶颈的统一信道韧性任务语义通信框架。该框架通过控制信息流以捕获细粒度特征级语义鲁棒性，对现有任务语义通信方法形成有效补充。针对实时子信道分配的案例研究实验验证了该框架的有效性。