  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.
