Compressive channel estimation and tracking for large arrays in mm wave picocells
Zhinus Marzi, Dinesh Ramasamy, Upamanyu Madhow

TL;DR
This paper introduces a compressive architecture for efficient estimation and tracking of sparse millimeter-wave channels in large antenna arrays, enabling accurate channel state information with minimal overhead in picocellular networks.
Contribution
It proposes a novel compressive beaconing method using pseudorandom phase settings and a sequential frequency estimation algorithm suitable for large arrays with phase-only control.
Findings
Achieves less than 1% overhead for large arrays
Provides accurate 2D spatial frequency estimation
Compatible with coarse phase control
Abstract
We propose and investigate a compressive architecture for estimation and tracking of sparse spatial channels in millimeter (mm) wave picocellular networks. The base stations are equipped with antenna arrays with a large number of elements (which can fit within compact form factors because of the small carrier wavelength) and employ radio frequency (RF) beamforming, so that standard least squares adaptation techniques (which require access to individual antenna elements) are not applicable. We focus on the downlink, and show that "compressive beacons," transmitted using pseudorandom phase settings at the base station array, and compressively processed using pseudorandom phase settings at the mobile array, provide information sufficient for accurate estimation of the two-dimensional (2D) spatial frequencies associated with the directions of departure of the dominant rays from the base…
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