Network signal control is an important means to tackle congestion in urban networks. This study proposes a model predictive control (MPC) approach for optimizing road network signal timing by employing an extended link transmission model with dynamic queues, namely the link queue transmission model (LQM). The LQM circumvents the limitations of the link transmission model that only considers link-level cumulative inflows and outflows at road boundaries. By incorporating turn-level queue dynamics across multiple turning directions, the LQM captures time-varying queues and spillback effects over the prediction horizon and enables the network controller to determine the green time fraction for all links centrally to minimize total queue length and reduce oscillations in signal plans. Simulation experimental results conducted on a grid network with six intersections demonstrate the effectiveness of the proposed method in reducing congestion compared to conventional methods.