  The explosive growth of data results in more scarce spectrum resources. It is
important to optimize the system performance under limited resources. In this
paper, we investigate how to achieve weighted throughput (WTP) maximization for
cell-free (CF) multiuser MIMO (MU-MIMO) multicarrier (MC) systems through
resource allocation (RA), in the cases of finite blocklength (FBL) and infinite
blocklength (INFBL) regimes. To ensure the quality of service (QoS) of each
user, particularly for the block error rate (BLER) and latency in the FBL
regime, the WTP gets maximized under the constraints of total power consumption
and required QoS metrics. Since the channels vary in different subcarriers
(SCs) and inter-user interference strengths, the WTP can be maximized by
scheduling the best users in each time-frequency (TF) resource and advanced
beamforming design, while the resources can be fully utilized. With this
motivation, we propose a joint user scheduling (US) and beamforming design
algorithm based on the successive convex approximation (SCA) and gene-aided
(GA) algorithms, to address a mixed integer nonlinear programming (MINLP)
problem. Numerical results demonstrate that the proposed RA outperforms the
comparison schemes. And the CF system in our scenario is capable of achieving
higher spectral efficiency than the centralized antenna systems (CAS).
