Statistical Beamforming on the Grassmann Manifold for the Two-User Broadcast Channel
Vasanthan Raghavan, Stephen Hanly, Venugopal Veeravalli

TL;DR
This paper develops a statistical beamforming method on the Grassmann manifold for a two-user MIMO broadcast channel with only statistical channel information at the transmitter, maximizing ergodic sum-rate.
Contribution
It introduces a closed-form ergodic sum-rate expression and an optimal beamforming solution based on dominant generalized eigenvectors, extending single-user covariance strategies.
Findings
Closed-form ergodic sum-rate expression derived
Optimal beamforming vectors are dominant generalized eigenvectors
Method extends to M-user MIMO broadcast channels
Abstract
A Rayleigh fading spatially correlated broadcast setting with M = 2 antennas at the transmitter and two-users (each with a single antenna) is considered. It is assumed that the users have perfect channel information about their links whereas the transmitter has only statistical information of each user's link (covariance matrix of the vector channel). A low-complexity linear beamforming strategy that allocates equal power and one spatial eigen-mode to each user is employed at the transmitter. Beamforming vectors on the Grassmann manifold that depend only on statistical information are to be designed at the transmitter to maximize the ergodic sum-rate delivered to the two users. Towards this goal, the beamforming vectors are first fixed and a closed-form expression is obtained for the ergodic sum-rate in terms of the covariance matrices of the links. This expression is non-convex in the…
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