  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 superior 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).
