On-the-fly Large-scale Channel-Gain Estimation for Massive Antenna-Array Base Stations
Abstract
We propose a novel scheme for estimating the large-scale gains of the channels between user terminals (UTs) and base stations (BSs) in a cellular system. The scheme leverages TDD operation, uplink (UL) training by means of properly designed non-orthogonal pilot codes, and massive antenna arrays at the BSs. Subject to Q resource elements allocated for UL training and using the new scheme, a BS is able to estimate the large-scale channel gains of K users transmitting UL pilots in its cell and in nearby cells, provided K<=Q^2. Such knowledge of the large-scale channel gains of nearby out-of-cells users can be exploited at the BS to mitigate interference to the out-of-cell users that experience the highest levels of interference from the BS. We investigate the large-scale gain estimation performance provided by a variety of non-orthogonal pilot codebook designs. Our simulations suggest that among all the code designs considered, Grassmannian line-packing type codes yield the best large-scale channel gain estimation performance.
Cite
@article{arxiv.1811.02202,
title = {On-the-fly Large-scale Channel-Gain Estimation for Massive Antenna-Array Base Stations},
author = {Chenwei Wang and Ozgun Y. Bursalioglu and Haralabos Papadopoulos and Giuseppe Caire},
journal= {arXiv preprint arXiv:1811.02202},
year = {2018}
}
Comments
6 pages, 3 figures, and published in IEEE ICC 2018