Revolutionizing Data Transmission - A Comprehensive Review of Deep Learning-Based Routing Mechanism for 5G Wireless Sensor Networks

The convergence of 5G technology and Wireless Sensor Networks (WSNs) has lead in a transformative era in wireless communication, demanding intelligent and adaptive routing protocols. This review explores into the monarchy of deep learning-based routing protocols, dissecting their potential applications, challenges, and impact on the efficiency of 5G-enabled WSNs. Lack of understanding and variance, two crucial factors in the details of deep learning-based routing. The review scrutinizes the complexity of routing decisions and explores how deep learning algorithms introduce a layer of adaptability significant of human perception. As we examine the landscape of 5G WSNs, the benefits and challenges of incorporating deep learning into routing practices come to light. Adaptive decision-making, energy efficiency, resilience to dynamic environments, and enhanced data accuracy emerge as promising outcomes. However, the review also sheds light on the computational complexities and potential biases in training data that necessitate careful consideration. This review serves as a compass, navigating through the terrain of deep learning-based routing protocols for 5G WSNs. By sorting out the hints of incomprehension and variance within this context, we aim to provide a comprehensive understanding of the evolving landscape of intelligent routing. As 5G technology continues to redefine connectivity standards, this review contributes to the foundation of knowledge guiding the development and implementation of effective and adaptive routing protocols in the era of wireless sensor networks.