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.

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