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.
翻译:多重存取 (MA) 设计是为了促进新兴语义传输和传统比特传输在未来网络中共存而调查的多重访问 (MA) 设计, 以方便正在形成的语义传输和传统比特传输在未来网络中的共存。 语义率是用来衡量语义传输的性能的考虑。 但是, 关键的挑战在于关键参数缺乏封闭式表达式, 即语义相似性, 其特征是原句和相应已恢复的句子之间的语义相似性。 为了克服这一挑战, 我们提议了一种数据回归法, 其语义相似性为普遍后勤功能所近似。 我们提议了一个混杂的语义和比特传输框架, 具体地说, 一个连接点将语义和比特传输的流发送到一个语义化用户( S- us) 。 为了在多用户网络中认识到这种混杂的语义和位传输的语义, 三种MA 系统( OMMA ) 和 半自动传输的比特流的语系分配, 将S- IMMA 的流和 亚频段 的亚流 系统 系统 演示的系统 演示图解 演示图显示为两个流 。