  Fast millimeter wave (mmWave) channel estimation techniques based on
compressed sensing (CS) suffer from low signal-to-noise ratio (SNR) in the
channel measurements, due to the use of wide beams. To address this problem, we
develop an in-sector CS-based mmWave channel estimation technique that focuses
energy on a sector in the angle domain. Specifically, we construct a new class
of structured CS matrices to estimate the channel within the sector of
interest. To this end, we first determine an optimal sampling pattern when the
number of measurements is equal to the sector dimension and then use its
subsampled version in the sub-Nyquist regime. Our approach results in low
aliasing artifacts in the sector of interest and better channel estimates than
benchmark algorithms.
