Control and communication are often tightly coupled for networked mobile robots; motions of robots impact communication quality and communication quality of service (QoS), in turn, affecting coordination performance of robots. In this article, we propose a theoretical motion planning control framework for a team of networked mobile robots to accomplish high-level spatial and temporal motion specifications while optimizing communication QoS. Desired motion specifications are formulated as signal temporal logic (STL), whereas the communication QoS to be optimized is captured by spatial temporal reach and escape logic (STREL) formulas. Both the STL and STREL specifications are encoded as mixed integer linear constraints posed on the system and environment state variables of the mobile robot network, where satisfactory control strategies can be computed by exploiting a distributed model predictive control (MPC) approach. A two-layer hierarchical MPC procedure is proposed to efficiently solve the co-optimization problem, whose recursive feasibility is formally ensured. The effectiveness of the proposed framework is validated by simulation.