Heterogeneous Semantic and Bit Communications: A Semi-NOMA Scheme
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Abstract (arXiv)
Multiple access (MA) design is investigated for facilitating the coexistence of the emerging semantic transmission and the conventional bit-based transmission in future networks. The semantic rate is considered for measuring the performance of the semantic transmission. However, a key challenge is that there is a lack of a closed-form expression for a key parameter, namely the semantic similarity, which characterizes the sentence similarity between an original sentence and the corresponding recovered sentence. To overcome this challenge, we propose a data regression method, where the semantic similarity is approximated by a generalized logistic function. Using the obtained tractable function, we propose a heterogeneous semantic and bit communication framework, where an access point simultaneously sends the semantic and bit streams to one semantics-interested user (S-user) and one bit-interested user (B-user). To realize this heterogeneous semantic and bit transmission in multi-user networks, three MA schemes are proposed, namely orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), and semi-NOMA. More specifically, the bit stream in semi-NOMA is split into two streams, one is transmitted with the semantic stream over the shared frequency sub-band and the other is transmitted over the separate orthogonal frequency sub-band. To study the fundamental performance limits of the three proposed MA schemes, the semantic-versus-bit (SvB) rate region and the power region are defined. An optimal resource allocation procedure is then derived for characterizing the boundary of the SvB rate region and the power region achieved by each MA scheme. The structures of the derived solutions demonstrate that semi-NOMA is superior to both NOMA and OMA given its highly flexible transmission policy. Our numerical results validate the analysis and show the superiority of semi-NOMA.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 May 2022.
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Citing papers per year: 2023: 4; 2024: 2; 2025: 1.
7 papers.
- 2023Optimization of Image Transmission in a Cooperative Semantic Communication Networkscited by 8
- 2023Performance Limits of a Deep Learning-Enabled Text Semantic Communication under Interferencecited by 6
- 2023Non-Orthogonal Multiple Access Enhanced Multi-User Semantic Communicationcited by 6
- 2025Low-Complexity Semantic Packet Aggregation for Token Communication via Lookahead Searchcited by 5
- 2024Deploying Foundation Model Powered Agent Services: A Surveycited by 4
- 2023A Relay System for Semantic Image Transmission based on Shared Feature Extraction and Hyperprior Entropy Compressioncited by 1
- 2024Hybrid Bit and Semantic Communicationscited by 0
- 2025Low-Complexity Semantic Packet Aggregation for Token Communication via Lookahead Search24 Jun 2025
- 2024Deploying Foundation Model Powered Agent Services: A Survey18 Dec 2024
- 2024Hybrid Bit and Semantic Communications30 Apr 2024
- 2023A Relay System for Semantic Image Transmission based on Shared Feature Extraction and Hyperprior Entropy Compression17 Nov 2023
- 2023Non-Orthogonal Multiple Access Enhanced Multi-User Semantic Communication12 Mar 2023
- 2023Performance Limits of a Deep Learning-Enabled Text Semantic Communication under Interference15 Feb 2023
- 2023Optimization of Image Transmission in a Cooperative Semantic Communication Networks1 Jan 2023