Machine Learning Tackles IoT Network Congestion: A Breakthrough in Collision Detection

Introduction  The exponential growth of IoT devices connected across various domains—smart cities, industrial automation, healthcare, and beyond—has led to unprecedented network congestion challenges. These devices, often low-power and sporadically transmitting data, rely heavily on cellular network infrastructures, especially in 4G LTE and emerging 5G networks, for reliable connectivity.  A critical bottleneck in this ecosystem is the Random Access Channel (RACH), which manages the initial connection requests from IoT devices to cellular towers. When thousands of devices attempt to connect simultaneously—a typical scenario in dense urban environments—the risk of signal collisions surges, causing delays and inefficiency. Collisions occur when multiple devices select the same preamble (a unique…
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