Machine Learning Revolutionizes Path Loss Modeling with Simplified Features

Accurate propagation modeling is paramount for effective radio deployments, coverage analysis, and interference mitigation in wireless communications. Path loss modeling, a widely adopted approach, enables generic predictions of signal power attenuation along wireless links, equipping network planners with essential insights into physical layer attributes. However, in non-line-of-sight (NLOS) scenarios, traditional models like Longley-Rice and free […]

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