Single-Sided Adaptive Estimation of Multi-Path Millimeter Wave Channels
Ahmed Alkhateeb, Omar ElAyach, Geert Leus, and Robert W. Heath, Jr.
in Proc. of the 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), vol., no., pp.125,129, 22-25 June 2014.
Millimeter wave (mmWave) cellular systems will
enable ultra high data rates by communicating over the large
bandwidth available in mmWave frequencies. To overcome the
channel propagation characteristics in this frequency band, large
antenna arrays need to be deployed at both the base station
and mobile users. While these large arrays provide sufficient
beamforming gains to meet the required link margins, they
make it challenging to estimate the mm Wave channel. In this
paper, we propose a mm Wave channel estimation algorithm that
exploits the sparse nature of the channel and leverages tools from
adaptive compressed sensing to efficiently estimate the channel
with a small training overhead. The proposed algorithm considers
practical hardware constraints on the training beamforming
design, and does not require the availability of a feedback channel
between the base station and the mobile user. Simulation results
indicate that comparable precoding gains can be achieved by the
proposed channel estimation algorithm relative to the case when
perfect channel knowledge exists.
Available on IEEE