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Semantic Communications Services within Generalist Operated Networks

Quentin Lampin, Louis-Adrien Dufrène, Guillaume Larue

TL;DR

The paper tackles the misalignment between operated networks' network-centric KPIs and application-level semantic needs. It proposes a framework with three core enablers: non-arbitrary semantic representations (embeddings), a standardized semantic Application-Network Interface with Semantic SLAs, and a semantic control plane for signaling and distributed learning. It introduces the Fragment-Quantize-Index (FQI) scheme for semantic-preserving transmission and a benchmark-based configuration approach to adapt to channel conditions, demonstrated on text-representation tasks. Results show up to approximately 128x reduction in transmitted resources for embeddings with only a modest overhead (2–3x) compared with UTF-8 text, while preserving task performance, indicating practical potential for end-to-end semantic transmission in operated networks. The work also outlines future directions on optimizing FQI, formalizing SSLAs, addressing privacy, and expanding integration scenarios.

Abstract

This paper addresses the challenge of integrating semantic communication principles into operated networks, traditionally optimized based on network-centric metrics rather than application-specific needs. Operated networks strongly adhere to the principle of ``separation of concerns", which emphasizes a clear distinction between network operation and application. Despite the initial perceived incompatibility between semantic communication and the principles of operated networks, this paper provides solutions to reconcile them. The foundations of these solutions include the adoption of non-arbitrary semantic representations as a standard encoding for communications, the establishment of a standard interface between the application and network, and a dedicated network control plane. These enable the application to describe the data typology and the nature of the task, and to agree upon a transmission scheme tailored to the supported task. Through three scenarios involving an application transmitting text representations, we illustrate the implementation of the proposal and demonstrate the potential of the approach.

Semantic Communications Services within Generalist Operated Networks

TL;DR

The paper tackles the misalignment between operated networks' network-centric KPIs and application-level semantic needs. It proposes a framework with three core enablers: non-arbitrary semantic representations (embeddings), a standardized semantic Application-Network Interface with Semantic SLAs, and a semantic control plane for signaling and distributed learning. It introduces the Fragment-Quantize-Index (FQI) scheme for semantic-preserving transmission and a benchmark-based configuration approach to adapt to channel conditions, demonstrated on text-representation tasks. Results show up to approximately 128x reduction in transmitted resources for embeddings with only a modest overhead (2–3x) compared with UTF-8 text, while preserving task performance, indicating practical potential for end-to-end semantic transmission in operated networks. The work also outlines future directions on optimizing FQI, formalizing SSLAs, addressing privacy, and expanding integration scenarios.

Abstract

This paper addresses the challenge of integrating semantic communication principles into operated networks, traditionally optimized based on network-centric metrics rather than application-specific needs. Operated networks strongly adhere to the principle of ``separation of concerns", which emphasizes a clear distinction between network operation and application. Despite the initial perceived incompatibility between semantic communication and the principles of operated networks, this paper provides solutions to reconcile them. The foundations of these solutions include the adoption of non-arbitrary semantic representations as a standard encoding for communications, the establishment of a standard interface between the application and network, and a dedicated network control plane. These enable the application to describe the data typology and the nature of the task, and to agree upon a transmission scheme tailored to the supported task. Through three scenarios involving an application transmitting text representations, we illustrate the implementation of the proposal and demonstrate the potential of the approach.

Paper Structure

This paper contains 11 sections, 4 figures.

Table of Contents

  1. Introduction
  2. A Network Operator Perspective
  3. Non-Arbitrary Semantic Representations
  4. Enhanced Application-Network Interface
  5. The case for semantic network integration
  6. Arbitrary data format over a non-semantic network
  7. Non-Arbitrary Data Transmission over a Semantic Network
  8. The FQI Scheme - Semantic Preserving Transmission
  9. Benchmark-based Network Configuration
  10. Scenarios Comparison
  11. Conclusion and Perspectives

Figures (4)

  • Figure 1: Operated Semantic Network Architecture
  • Figure 2: FQI scheme illustration over BSC: Fragmented embedding coordinates are projected onto the nearest centroid, then sent as binary codes over the logical channel. Since channel errors may cause reconstruction errors in the semantic space without preserving error locality, it is crucial to properly design the FQI scheme. For instance, under shown mapping, errors more likely result in the reception of centroids $c_1$ or $c_3$ rather than the semantically closer $c_0$ during transmission of embedding $e$.
  • Figure 3: FQI evaluation summary: model accuracy against BER and (d,b) configurations. Nominal model accuracy is 0.8660. Acceptable accuracy loss is fixed at 95% of nominal accuracy.
  • Figure 4: Network resources required for transmitting customer's inquiries: FQI vs arbitrary binary data transmission