A Novel Call Admission Control for 5G Communication with Efficient Handoff

The emergence of 5G networks has brought for the unprecedented demands for high data rates, low latency, and seam less connectivity, particularly in densely populated and high-mobility scenarios. Traditional call admission control (CAC) mechanisms often struggle to maintain consistent quality of service (QoS) during hand off processes, leading to increased call drops and disruptions. This paper proposes an optimized CAC algorithm tailored specifically for 5G environments, aiming to enhance hand off efficiency and connection reliability across dynamic network conditions. The proposed solution employs a hybrid model combining dynamic resource allocation and predictive analytics to intelligently prioritize hand off processes and manage admission control based on real-time user mobility and network traffic patterns. Simulation results demonstrate the effectiveness of this approach in significantly reducing hand off latency and call drop rates, outperforming conventional CAC schemes. The findings underline the algorithm's capability to adapt to 5G's ultra-dense network demands, supporting seam less connectivity and improved QoS. This novel CAC frame work offers a promising solution for handling resource allocation and hand off challenges in 5G, paving the way for further advancements in next-generation wireless communication.