🤖 AI Summary
This study addresses the dual-fidelity rate–distortion trade-off for structured semantic sources in task-oriented communication. By restricting to deterministic intra-class encoding mappings and integrating conditional mean decoding with the Lloyd–Max stationarity conditions, the paper derives fundamental rate–distortion characteristics. It innovatively constructs the first dual-purpose feasibility band tailored to such semantic sources, revealing upper and lower bounds on achievable communication rates under non-single-letter fidelity criteria and their dependence on partition cardinality, thereby extending the Shannon–Kolmogorov (SK) framework. Theoretically, it proves that the intra-class SK rate is no less than the maximum of the corresponding Shannon rate–distortion function. In an aggregation validation scenario, a feasibility band of width $\log_2(K_{\max}/K_{\min})$ bits is obtained, with empirical validation provided through a smart grid economic dispatch case study.
📝 Abstract
The joint rate-distortion framework of Stavrou and Kountouris (IEEE Transactions on Communications 2023) characterises dual-fidelity tradeoffs for semantic communication on stochastic semantic sources. Many task-oriented communication systems instead use designed sources, where the semantic object is a deterministic oracle allocation $φ^(t)$ rather than a stochastic quantity given by nature. We isolate the subclass of designed sources under smooth concave utility with assumptions A1, A2 and Euclidean allocation codomain, and restrict the encoder class to deterministic common-category mappings. Within this subclass the SK exponential-tilting decoder and generalised Blahut--Arimoto iteration specialise to conditional-mean decoding and Lloyd--Max stationarity on $φ^(t)$. When the second fidelity is a monotone single-letter distortion, the joint problem stays inside the SK admissible class; the common-category SK rate is lower-bounded by the max of the corresponding Shannon rate-distortion functions, with equality only when the common-category reconstruction is compatible and RDF-optimal. When the second fidelity is aggregate verification, the joint problem leaves the SK single-letter class and admits a constrained-design feasibility band $R_{\min}(\varepsilon^) \leq R \leq R_{\max}(β^)$ of width $\log_2(K_{\max}/K_{\min})$ bits in partition cardinality. The reduction and the band are scope statements on the SK apparatus, not modifications to it. A smart-grid economic-dispatch example with a non-technical-loss-detection contrast illustrates the band.