  Compressed beamforming algorithm is used in the current Wi-Fi standard to
reduce the beamforming feedback overhead (BFO). However, with each new
amendment of the standard the number of supported antennas in Wi-Fi devices
increases, leading to increased BFO and hampering the throughput despite using
compressed beamforming. In this paper, a novel index-based method is presented
to reduce the BFO in Wi-Fi links. In particular, a k-means clustering-based
approach is presented to generate candidate beamforming feedback matrices,
thereby reducing the BFO to only the index of the said candidate matrices. With
extensive simulation results, we compare the newly proposed method with the
IEEE 802.11be baseline and our previously published index-based method. We show
approximately 54% gain in throughput at high signal-to-noise (SNR) against the
IEEE 802.11be baseline. Our comparison also shows approximately 4 dB gain
compared to our previously published method at the packet-error-rate (PER) of
0.01 using MCS index 11. Additionally, we also discuss the impact of the
distance metric chosen for clustering as well as candidate selection on the
link performance.
