Wireless communication systems must evolve to meet the increasing demand for advanced services and connected devices. Future wireless networks aim to provide wider connectivity, enabling smarter devices to operate over broader frequency bands. This development will benefit Networked Control System (NCS) applications, including telemedicine, smart grids, teleoperation, and autonomous vehicles, with stringent latency and reliability requirements. However, a proper understanding of NCS’s dynamic behavior is necessary to prevent indiscriminate communications resource usage, leading to scarcity as the number of users increases. Communications-Control Co-Design (CoCoCo) strategies would leverage the dynamic knowledge of the system to adapt the communications resource usage depending on their availability by switching between control strategies and communications policies to ensure Quality-of-Service (QoS) and Quality-of-Control (QoC). As multiple variables parameterize the control and communications systems, the CoCoCo can be simplified by abstracting the dependencies of each design parameter on the sampling period, link latency, and packet loss probability. Determining the operation boundaries of these parameters provides a guideline to ensure the QoC based on the QoS that a communications policy can provide. Therefore, using a robustness analysis of the norm of the NCS based on the imperfections introduced by the communications systems, the Maximum Allowable Transmission Interval (MATI), Maximum Allowable Delay (MAD), and Maximum Allowable Packet Loss Probability (MAPLP) can be derived. This thesis proposes a methodology for calculating MATI and deriving analytical solutions for MAD and MAPLP for general NCS. These bounds are evaluated in the longitudinal platoon case for the Cooperative Adaptive Cruise Control (CACC) case to ensure robust performance against unwanted amplified oscillations referred to as string instability. The bounds of the communications requirements are evaluated using a Lyapunov function and a discrete stochastic transfer function, which show a close fit between the two approaches, implying an accurate estimation of the H8 norm. This work demonstrates the relevance of MATI as a normalization factor that abstracts the robustness regions of NCS and allows their comparison. The proposed methodology also shows a less conservative estimate of the MAPLP by at least one order of magnitude when the system transmits at a rate lower than the inverse of the MATI compared to the state-of-the-art. This work proposes two control methods called Estimator Enhanced Cooperative Adaptive Cruise Control (EECACC) and Predictive CACC (PCACC) to relax the limits of the communications resources while allowing the adaptability of the CoCoCo approach. The EECACC exploits the use of Kalman filters to encode and decode the transmitted information using the estimation error and shows that, based on the assumed correlation of acceleration, the improvements over the MATI range from 21% to 238%. Conversely, the PCACC architecture evaluates how predictions can relax communications requirements and shows that predictions provide a gain that increases as the number of predictions increases. However, inconsistencies in the predictions can reduce this gain to the point where it becomes a hindrance. These different architectures provide flexibility for selecting which control strategy and communications policy guarantees the QoS and QoC of multiple users and optimally assign communications resources for NCS, laying the foundation for CoCoCo methodologies for platooning and other NCS applications.