Resource allocation for text semantic communications

TL;DR

This paper introduces the concept of semantic spectral efficiency (S-SE) for text communication, proposing resource allocation strategies that enhance reliability and efficiency in semantic communications, especially under low SNR conditions.

Contribution

It defines the novel S-SE metric and develops resource allocation methods based on it, filling a gap in semantic communication resource management.

Findings

Semantic spectral efficiency (S-SE) is effective for optimizing resource allocation.

Semantic communications outperform conventional systems in S-SE.

The proposed method improves transmission reliability and efficiency.

Abstract

Semantic communications have shown its great potential to improve the transmission reliability, especially in the low signal-to-noise regime. However, resource allocation for semantic communications still remains unexplored, which is a critical issue in guaranteeing the semantic transmission reliability and the communication efficiency. To fill this gap, we investigate the spectral efficiency in the semantic domain and rethink the semantic-aware resource allocation issue. Specifically, taking text semantic communication as an example, the semantic spectral efficiency (S-SE) is defined for the first time, and is used to optimize resource allocation in terms of channel assignment and the number of transmitted semantic symbols. Additionally, for fair comparison of semantic and conventional communication systems, a transform method is developed to convert the conventional bit-based spectral efficiency to the S-SE. Simulation results demonstrate the validity and feasibility of the proposed resource allocation method, as well as the superiority of semantic communications in terms of the S-SE.