Low Complexity Channel Estimation Based on DFT for Short Range Communication

Authors:
Gaojian Wang, Shaghayegh Aghabozorgi Naeimi, and Gerd Ascheid
Book Title:
Proceedings of IEEE International Conference on Communications (ICC)
Pages:
1–7
Date:
May 2017
DOI:
10.1109/ICC.2017.7996917
Language:
English
Copyright:
©2017  IEEE

BibTeX

@inproceedings{wang17,
author = {Gaojian Wang, Shaghayegh Aghabozorgi Naeimi, and Gerd Ascheid},
booktitle = {Proceedings of IEEE International Conference on Communications (ICC)},
title = {Low Complexity Channel Estimation Based on DFT for Short Range Communication},
year = {2017},
month = {may},
pages = {1-7},
doi = {10.1109/ICC.2017.7996917},
}

Abstract

In a practical large scale antenna system (LSAS) over the millimeter Wave (mmWave) bands, the implementation of hybrid beamforming structure plays an important role as it provides high precoding gains to overcome the high path loss and achieve sufficient link margins. While employing such large antenna arrays, it becomes challenging to estimate the mmWave channel using the conventional algorithms. In this paper, we develop two novel multi-resolution mmWave channel estimation algorithms that exploit two dimensional discrete Fourier transform technique inspired by the sparse nature of the mmWave channel. The proposed algorithms take into account practical radio frequency (RF) hardware limitations and computational complexity reduction during the training phases. Numerical results indicate that the proposed algorithms can achieve a comparable spectral efficiency with respect to the case when perfect channel state information is known.

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