WebJun 1, 2011 · In this context, the sum-rate of non-orthogonal OBF with N> N t beams are studied, where the transmitter is based on the Grassmannian beamforming. Our results show that non-orthogonal OBF is an... WebChannel Estimation-Free Deep Direct Beamforming with Low Complexity in mmWave Massive MIMO. ... Joint Interference Alignment Precoding based on the Optimization Algorithm on the Grassmannian Manifold. 2024 - Li, ...
Grassmannian beamforming for MIMO AF relaying Request …
WebJan 27, 2024 · In this paper, we show that this approach can effectively be enhanced by DNN classification to further reduce the implementation complexity and, thus, support high resolution Grassmannian... WebMar 1, 2006 · A new quantizer design criterion for capacity maximization is proposed and the corresponding iterative vector quantization (VQ) design algorithm is developed and supported by computer simulations. This paper investigates quantization methods for feeding back the channel information through a low-rate feedback channel in the context … imx6ull uboot2022
Grassmannian Beamforming for MIMO Amplify-and …
WebMay 17, 2024 · The key technical contribution lies in reducing the codebook design problem to an unsupervised clustering problem on a Grassmann manifold where the cluster centroids form the finite-sized... WebMay 28, 2024 · Grassmannian frames consist of unit-norm vectors with a maximum cross correlation between each other that is minimal. A property like that is desired in many applications, such as in wireless communications, sparse recovery, quantum information theory, and more. WebTheorem 1: The optimal values of the source beamforming vector, the destination combining vector, and the relay weight- ing matrix for the problem in (4) are given by: s⋆=b1, r⋆=f1, W⋆=σg1a1H, where we have used the SVD equations in (3), and σ= 1+P1φ2 1 −1 2. Note that W⋆is a rank one matrix. Proof: The optimization is accomplished in two steps. imx8 smarc