AI for beam management: ML-predicted beams, reduced overhead, faster tracking

The Beam Management Challenge

In 5G NR, massive MIMO and mmWave systems use narrow directional beams to overcome path loss and increase spectral efficiency. Traditional beam management requires exhaustive beam sweeping — the gNB transmits reference signals on every candidate beam, and the UE measures and reports the best ones. With 64 or more beams per panel, this process consumes significant overhead in reference signal transmissions and reporting latency. For mmWave with 256-beam codebooks, the overhead becomes prohibitive, especially for mobile users where the optimal beam changes rapidly as the UE moves.