Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling

In this paper, we address the problem of joint downlink (DL) and uplink (UL) channel estimation for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Assuming a closed-loop and multifrequency-based channel training framework in which pilot signals received by multiple antenna m...

Full description

Bibliographic Details
Main Authors: Paulo R. B. Gomes, André L. F. de Almeida, João Paulo C. L. da Costa, Rafael T. de Sousa
Format: Article
Language:English
Published: Hindawi-Wiley 2019-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2019/4858137
id doaj-980bcc6593324679b9e066445d4cf6da
record_format Article
spelling doaj-980bcc6593324679b9e066445d4cf6da2020-11-25T02:06:40ZengHindawi-WileyWireless Communications and Mobile Computing1530-86691530-86772019-01-01201910.1155/2019/48581374858137Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor ModelingPaulo R. B. Gomes0André L. F. de Almeida1João Paulo C. L. da Costa2Rafael T. de Sousa3Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza-CE, BrazilDepartment of Teleinformatics Engineering, Federal University of Ceará, Fortaleza-CE, BrazilDepartment of Electrical Engineering, University of Brasília, Brasília-DF, BrazilDepartment of Electrical Engineering, University of Brasília, Brasília-DF, BrazilIn this paper, we address the problem of joint downlink (DL) and uplink (UL) channel estimation for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Assuming a closed-loop and multifrequency-based channel training framework in which pilot signals received by multiple antenna mobile stations (MSs) are coded and spread in the frequency domain via multiple adjacent subcarriers, we propose two tensor-based semiblind receivers by capitalizing on the multilinear structure and sparse feature of the received signal at the BS equipped with a hybrid analog-digital beamforming (HB) architecture. As a first processing stage, the joint estimation of the compressed DL and UL channel matrices can be obtained in an iterative way by means of an alternating least squares (ALS) algorithm that capitalizes on a parallel factors model for the received signals. Alternatively, for more restricted scenarios, a closed-form solution is also proposed. From the estimated effective channel matrices, the users’ channel parameters such as angles of departure (AoD), angles of arrival (AoA), and path gains are then estimated in a second processing stage by solving independent compressed sensing (CS) problems (one for each MS). In contrast to the classical approach in the literature, in which the DL and UL channel estimation problems are usually considered as two separate problems, our idea is to jointly estimate both the DL and UL channels as a single problem by concentrating most of the processing burden for channel estimation at the BS side. Simulation results demonstrate that the proposed receivers achieve a performance close to the classical approach that is applied on DL and UL communication links separately, with the advantage of avoiding complex computations for channel estimation at the MS side as well as dedicated feedback channels for each MS, which are attractive features for massive MIMO systems.http://dx.doi.org/10.1155/2019/4858137
collection DOAJ
language English
format Article
sources DOAJ
author Paulo R. B. Gomes
André L. F. de Almeida
João Paulo C. L. da Costa
Rafael T. de Sousa
spellingShingle Paulo R. B. Gomes
André L. F. de Almeida
João Paulo C. L. da Costa
Rafael T. de Sousa
Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling
Wireless Communications and Mobile Computing
author_facet Paulo R. B. Gomes
André L. F. de Almeida
João Paulo C. L. da Costa
Rafael T. de Sousa
author_sort Paulo R. B. Gomes
title Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling
title_short Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling
title_full Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling
title_fullStr Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling
title_full_unstemmed Joint DL and UL Channel Estimation for Millimeter Wave MIMO Systems Using Tensor Modeling
title_sort joint dl and ul channel estimation for millimeter wave mimo systems using tensor modeling
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8669
1530-8677
publishDate 2019-01-01
description In this paper, we address the problem of joint downlink (DL) and uplink (UL) channel estimation for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Assuming a closed-loop and multifrequency-based channel training framework in which pilot signals received by multiple antenna mobile stations (MSs) are coded and spread in the frequency domain via multiple adjacent subcarriers, we propose two tensor-based semiblind receivers by capitalizing on the multilinear structure and sparse feature of the received signal at the BS equipped with a hybrid analog-digital beamforming (HB) architecture. As a first processing stage, the joint estimation of the compressed DL and UL channel matrices can be obtained in an iterative way by means of an alternating least squares (ALS) algorithm that capitalizes on a parallel factors model for the received signals. Alternatively, for more restricted scenarios, a closed-form solution is also proposed. From the estimated effective channel matrices, the users’ channel parameters such as angles of departure (AoD), angles of arrival (AoA), and path gains are then estimated in a second processing stage by solving independent compressed sensing (CS) problems (one for each MS). In contrast to the classical approach in the literature, in which the DL and UL channel estimation problems are usually considered as two separate problems, our idea is to jointly estimate both the DL and UL channels as a single problem by concentrating most of the processing burden for channel estimation at the BS side. Simulation results demonstrate that the proposed receivers achieve a performance close to the classical approach that is applied on DL and UL communication links separately, with the advantage of avoiding complex computations for channel estimation at the MS side as well as dedicated feedback channels for each MS, which are attractive features for massive MIMO systems.
url http://dx.doi.org/10.1155/2019/4858137
work_keys_str_mv AT paulorbgomes jointdlandulchannelestimationformillimeterwavemimosystemsusingtensormodeling
AT andrelfdealmeida jointdlandulchannelestimationformillimeterwavemimosystemsusingtensormodeling
AT joaopaulocldacosta jointdlandulchannelestimationformillimeterwavemimosystemsusingtensormodeling
AT rafaeltdesousa jointdlandulchannelestimationformillimeterwavemimosystemsusingtensormodeling
_version_ 1724932675616112640