@inproceedings{8c8a381954064d5f96c9eb259289a1c1,
title = "ADMM-Based Solution for mmWave UL Channel Estimation with One-Bit ADCs via Sparsity Enforcing and Toeplitz Matrix Reconstruction",
abstract = "Low-power millimeter wave (mmWave) multi-input multi-output communication systems can be enabled with the use of one-bit analog-to-digital converters. Owing to the extreme quantization, conventional signal processing tasks such as channel estimation are challenging, making uplink (UL) multiuser receivers difficult to implement. To address this issue, we first reformulate the UL channel estimation problem, and then combine the idea of ℓ1 regularized logistic regression classification and Toeplitz matrix reconstruction in a properly designed optimization problem. Our new method is referred to as ℓ1 regularized logistic regression with Toeplitz matrix reconstruction (L1-RLR-TMR). In addition, we develop a computationally efficient alternating direction method of multi-pliers (ADMM)-based implementation for the L1-RLR-TMR method. Numerical results demonstrate the performance of the L1-RLR-TMR method in comparison with other existing methods.",
keywords = "angular domain, Multi-user MIMO, one-bit ADC, Toeplitz matrix reconstruction, uplink channel estimation, ℓ regularized logistic regression",
author = "Majdoddin Esfandiari and Vorobyov, {Sergiy A.} and Heath, {Robert W.}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Conference on Communications, ICC ; Conference date: 28-05-2023 Through 01-06-2023",
year = "2023",
doi = "10.1109/ICC45041.2023.10279217",
language = "English",
series = "IEEE International Conference on Communications",
publisher = "IEEE",
pages = "1338--1343",
editor = "Michele Zorzi and Meixia Tao and Walid Saad",
booktitle = "ICC 2023 - IEEE International Conference on Communications",
address = "United States",
}