Massive device access for the Internet of Things (IoT) is one of the main services of 5G and 6G mobile networks via support for Massive Machine-Type Communications (mMTC).
One of the main problems in supporting mMTC is the collision of transmissions when accessing the network, which reduces network capacity, quality of service and gains for network operators.
The master's thesis entitled “Mechanisms for improving the performance of the random access procedure for mMTC in cellular IoT networks”, by student Giancarlo Maldonado Cardenas, supervised by Prof. Nelson Fonseca and co-supervised by Prof. Carlos Astudillo, aims to develop algorithms for detecting collisions in network access based on machine learning. The proposed techniques detect the presence of collisions with high accuracy, significantly increasing the number of IoT devices that can simultaneously access the network.
The student is a researcher at the Computer Network Laboratory (LRC).
#computer network
#5g #iot
@giancarlo16_