Efficient beamforming training scheme using NOMA in mmWave WLANs

Beamforming training (BFT) is a critical process for establishing directional links in millimeter-wave (mmWave) wireless local area networks. However, its performance significantly degrades due to frequent slot collisions. This paper proposes a non-orthogonal multiple access (NOMA)-based exhaustive search (NES) scheme, which allows multiple stations (STAs) to perform BFT concurrently by independently selecting predefined transmit power levels. We integrated the NOMA-based technique into a time-based beam collision avoidance (TBCA) scheme, named NOMA-TBCA (NTBCA). The proposed NES and NTBCA schemes are analytically modeled and evaluated through simulations. The results confirm that the combined approach effectively enhances the association probability and the throughput.