  Extremely large aperture arrays can enable unprecedented spatial multiplexing
in beyond 5G systems due to their extremely narrow beamfocusing capabilities.
However, acquiring the spatial correlation matrix to enable efficient channel
estimation is a complex task due to the vast number of antenna dimensions.
Recently, a new estimation method called the "reduced-subspace least squares
(RS-LS) estimator" has been proposed for densely packed arrays. This method
relies solely on the geometry of the array to limit the estimation resources.
In this paper, we address a gap in the existing literature by deriving the
average spectral efficiency for a certain distribution of user equipments (UEs)
and a lower bound on it when using the RS-LS estimator. This bound is
determined by the channel gain and the statistics of the normalized spatial
correlation matrices of potential UEs but, importantly, does not require
knowledge of a specific UE's spatial correlation matrix. We establish that
there exists a pilot length that maximizes this expression. Additionally, we
derive an approximate expression for the optimal pilot length under low
signal-to-noise ratio (SNR) conditions. Simulation results validate the
tightness of the derived lower bound and the effectiveness of using the
optimized pilot length.
