Semantic communication (SemCom) is emerging as a key technology for future sixth-generation (6G) systems. Unlike traditional bit-level communication (BitCom), SemCom directly optimizes performance at the semantic level, leading to supe- rior communication efficiency. Nevertheless, the task-oriented nature of SemCom renders it challenging to completely replace BitCom. Consequently, it is desired to consider a semantic-bit coexisting communication system, where a base station (BS) serves SemCom users (sem-users) and BitCom users (bit-users) simultaneously. Such a system faces severe and heterogeneous inter-user interference. In this context, this paper provides a new semantic-bit coexisting communication framework and proposes a spatial beamforming scheme to accommodate both types of users. Specifically, we consider maximizing the semantic rate for semantic users while ensuring the quality-of-service (QoS) requirements for bit-users. Due to the intractability of obtaining the exact closed-form expression of the semantic rate, a data driven method is first applied to attain an approximated expression via data fitting. With the resulting complex transcendental function, majorization minimization (MM) is adopted to convert the original formulated problem into a multiple-ratio problem, which allows fractional programming (FP) to be used to further transform the problem into an inhomogeneous quadratically constrained quadratic programs (QCQP) problem. Solving the problem leads to a semi-closed form solution with undetermined Lagrangian factors that can be updated by a fixed point algorithm. Extensive simulation results demonstrate that the proposed beamforming scheme significantly outperforms conventional beamforming algorithms such as zero-forcing (ZF), maximum ratio transmission (MRT), and weighted minimum mean-square error (WMMSE).

翻译：语义通信（SemCom）正成为未来第六代（6G）系统的关键技术。与传统比特级通信（BitCom）不同，SemCom直接在语义层面优化性能，从而显著提升通信效率。然而，SemCom的任务导向特性使其难以完全替代BitCom。为此，有必要考虑一种语义与比特共存的通信系统，其中基站（BS）同时服务SemCom用户（语义用户）和BitCom用户（比特用户）。此类系统面临严重且异构的用户间干扰。在此背景下，本文提出了一种新型语义与比特共存通信框架，并设计了一种空间波束赋形方案以兼容两类用户。具体而言，我们以最大化语义用户的语义速率为目标，同时保障比特用户的服务质量（QoS）要求。由于语义速率的精确闭式表达式难以获取，本文首先采用数据驱动方法，通过数据拟合获得近似表达式。针对所得复杂超越函数，利用最大最小化（MM）方法将原始问题转化为多比例问题，进而通过分数规划（FP）进一步转化为非齐次二次约束二次规划（QCQP）问题。对该问题的求解可得到含待定拉格朗日乘子的半闭式解，该乘子可通过不动点算法更新。大量仿真结果表明，所提波束赋形方案显著优于传统波束赋形算法，如迫零（ZF）、最大比传输（MRT）和加权最小均方误差（WMMSE）。