Design and Optimization of AI based 5G/6G Communication Protocols for Smart Cities

This research work focuses on the design and performance optimization of 5G/6G communication protocols for smart city environments using simulation. With the growing demand for ultra-reliable and low-latency communications in smart transportation, healthcare, and IoT systems, there is a critical need to enhance communication efficiency in dense urban networks. The study is conducted in two stages: a baseline simulation of a 5G/6G communication system and an AI-optimized model using Reinforcement Learning (RL). The baseline model measures standard parameters such as latency, throughput, and packet delivery ratio, while the AI-enhanced model dynamically adjusts communication parameters to improve performance. Simulation results indicate that the AI-optimized system reduces latency, increases throughput, and improves the packet delivery ratio compared to the baseline model, making it more suitable for real-time smart city applications.