Fundamental Limits of Adaptive Beamforming Under Finite Training
Finite training reduces the output signal-to-interference-plus-noise ratio (SINR) of an adaptive beamformer, and a natural question is how much of this loss is unavoidable. This paper determines this question, providing a beamforming counterpart of the Cram\'er--Rao bound in spectral estimation. An exact identity expre...