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Rate-Splitting Multiple Access for Coexistence of Semantic and Bit Communications

Yuanwen Liu, Bruno Clerckx

TL;DR

This work studies resource allocation for uplink coexistence of semantic and bit communications, introducing RSMA as a flexible MA scheme to manage interference while preserving semantic understandability. It defines a semantic rate metric via DeepSC-derived sentence similarity and a logistic surrogate to enable tractable optimization, expressed as $S=\frac{W I}{K L}\varepsilon(\rho)$. The authors derive rate regions for FDMA, NOMA, and RSMA under semantic constraints and develop SCA-based algorithms to compute boundary points, showing RSMA outperforms NOMA and often exceeds FDMA, with gains amplified by more semantic users and stricter semantic quality requirements. The results support RSMA as a viable mechanism for future 6G networks enabling coexistence of semantic and traditional bit services with adjustable semantic accuracy.

Abstract

In the sixth generation (6G) of cellular networks, the demands for capacity and connectivity will increase dramatically to meet the requirements of emerging services for both humans and machines. Semantic communication has shown great potential because of its efficiency, and suitability for users who only care about the semantic meaning. But bit communication is still needed for users requiring original messages. Therefore, there will be a coexistence of semantic and bit communications in future networks. This motivates us to explore how to allocate resources in such a coexistence scenario. We investigate different uplink multiple access (MA) schemes for the coexistence of semantic users and a bit user, namely orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) and rate-splitting multiple access (RSMA). We characterize the rate regions achieved by those MA schemes. The simulation results show that RSMA always outperforms NOMA and has better performance in high semantic rate regimes compared to OMA. We find that RSMA scheme design, rate region, and power allocation are quite different in the coexistence scenario compared to the bit-only communication, primarily due to the need to consider the understandability in semantic communications. Interestingly, in contrast to bit-only communications where RSMA is capacity achieving without any need for time sharing, in the coexistence scenario, time sharing helps enlarging RSMA rate region.

Rate-Splitting Multiple Access for Coexistence of Semantic and Bit Communications

TL;DR

This work studies resource allocation for uplink coexistence of semantic and bit communications, introducing RSMA as a flexible MA scheme to manage interference while preserving semantic understandability. It defines a semantic rate metric via DeepSC-derived sentence similarity and a logistic surrogate to enable tractable optimization, expressed as . The authors derive rate regions for FDMA, NOMA, and RSMA under semantic constraints and develop SCA-based algorithms to compute boundary points, showing RSMA outperforms NOMA and often exceeds FDMA, with gains amplified by more semantic users and stricter semantic quality requirements. The results support RSMA as a viable mechanism for future 6G networks enabling coexistence of semantic and traditional bit services with adjustable semantic accuracy.

Abstract

In the sixth generation (6G) of cellular networks, the demands for capacity and connectivity will increase dramatically to meet the requirements of emerging services for both humans and machines. Semantic communication has shown great potential because of its efficiency, and suitability for users who only care about the semantic meaning. But bit communication is still needed for users requiring original messages. Therefore, there will be a coexistence of semantic and bit communications in future networks. This motivates us to explore how to allocate resources in such a coexistence scenario. We investigate different uplink multiple access (MA) schemes for the coexistence of semantic users and a bit user, namely orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) and rate-splitting multiple access (RSMA). We characterize the rate regions achieved by those MA schemes. The simulation results show that RSMA always outperforms NOMA and has better performance in high semantic rate regimes compared to OMA. We find that RSMA scheme design, rate region, and power allocation are quite different in the coexistence scenario compared to the bit-only communication, primarily due to the need to consider the understandability in semantic communications. Interestingly, in contrast to bit-only communications where RSMA is capacity achieving without any need for time sharing, in the coexistence scenario, time sharing helps enlarging RSMA rate region.
Paper Structure (14 sections, 46 equations, 13 figures, 2 algorithms)

This paper contains 14 sections, 46 equations, 13 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. Semantic communication metric and approximation
  3. Semantic Communication Metric
  4. Data Regression Method For Semantic Rate Approximation
  5. System Model
  6. FDMA
  7. NOMA
  8. RSMA
  9. Numerical Results
  10. The rate regions for different numbers of semantic users
  11. Comparing RSMA behaviour for bit communications and for coexistence
  12. The advantages of RSMA with multiple semantic users
  13. The advantages of RSMA in high accuracy applications
  14. Conclusion

Figures (13)

  • Figure 1: The illustration of the framework of DeepSC.
  • Figure 2: The logistic regression for approximating $\varepsilon(\rho,K)$,
  • Figure 3: An illustration of semantic users and bit user coexistence.
  • Figure 4: The illustration of FDMA.
  • Figure 5: The illustration of NOMA.
  • ...and 8 more figures

Theorems & Definitions (2)

  • proof
  • proof