@inproceedings{7f5bcae3172f4ed39e1cd1bf94c5e6da,
title = "A Weighted MMSE Approach to Amorphous Cell for Mixed-ADC Distributed Massive MIMO",
abstract = " Distributed massive multi-input-multi-output (mMIMO) is a promising architecture which has potential to satisfy the strick latency requirement in Internet of Things (IoT). To further meet the low-cost and low-latency demand in IoT, this paper provides a low-complexity scheme to the access phase for mixed analog-to-digital convertors (ADC) distributed mMIMO. which consists of two steps. In the first step, the clustering behavior among users is detected using large scale fading information, which aims to reduce the complexity. In the second step, with the number of clusters as a priori, a weighted minimum mean square error (WMMSE) clustering algorithm that can provide stable and robust results is proposed. The clustering algorithm aims to maximize the achievable sum rate, in which the nonconvex objective function and constraints are modeled using ell 1 -norm approximation. Numerical results show that the proposed algorithm has strong convergence, and significant gain can be obtained in various scenarios. ",
keywords = "Distributed mMIMO, user clustering, weighted sum rate maximization",
author = "Jide Yuan and Qi He and Michail Matthaiou and Yuyang Wang and Quek, {Tony Q.S.} and Shi Jin",
year = "2019",
month = feb,
day = "19",
doi = "10.1109/ACSSC.2018.8645097",
language = "English",
isbn = "9781538692189",
volume = "2018-October",
series = "Asilomar Conference on Signals, Systems, and Computers: Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "969--974",
editor = "Matthews, {Michael B.}",
booktitle = "52nd Asilomar Conference on Signals, Systems and Computers (ACSSC 2018): Proceedings",
address = "United States",
note = "52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 ; Conference date: 28-10-2018 Through 31-10-2018",
}