Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
IEEE Wireless Communications Letters
We consider a downlink massive multiple-input multiple output system employing regularized zero-forcing precoding. We derive the asymptotic signal-to-leakage-plus-noise ratio (SLNR) as both the number of antennas and the number of users go to infinity at a fixed ratio. Focusing on spatially uncorrelated channels with homogeneous large scale fading gains, we show that the SLNR is asymptotically equal to signal-to-interference-plus-noise ratio, which allows us to optimize the user loading for spectral efficiency. The results show that the optimal user loading varies depending on the channel signal-to-noise ratio (SNR). As the SNR increases, the optimal user loading decreases at low SNR, but increases at high SNR.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
Ilkan Esiyok, Pascal Berrang, Katriel Cohn-Gordon, Robert Künnemann