TY - JOUR
T1 - Energy-Efficient Design for Massive MIMO with Hardware Impairments
AU - Liu, Zhihui
AU - Lee, Chia-Han
AU - Xu, Wenjun
AU - Li, Shengyu
N1 - Publisher Copyright:
© 2002-2012 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/2
Y1 - 2021/2
N2 - In this paper, an energy-efficient design for massive multiple-input multiple-output (MIMO) systems is studied with the consideration of hardware impairments. The objective is to maximize the system energy efficiency of both uplink and downlink transmissions by jointly optimizing the number of antennas at the base station, the number of served users, and the transmit power. Firstly, by considering the linear distortion due to hardware impairments, the resultant channel estimation error from both distortion and noise is analyzed, following which closed-form approximations for the average achievable uplink/downlink rates are derived. Then, a massive MIMO energy efficiency optimization problem considering hardware impairments is formulated. By applying the techniques of relaxation and change of variables, an alternative optimization with build-in bisection search (AO-BS) algorithm is proposed with the quasi-concavity of the transformed objective function theoretically proved. The performance of the proposed AO-BS algorithm is validated through numerical simulations, which shows fast convergence to near-optimal solutions. Compared with existing approaches, the proposed scheme improves the system energy efficiency greatly when the hardware impairments are considered. Furthermore, the system design guideline in terms of the number of antennas, the number of served users, and the transmit power is provided.
AB - In this paper, an energy-efficient design for massive multiple-input multiple-output (MIMO) systems is studied with the consideration of hardware impairments. The objective is to maximize the system energy efficiency of both uplink and downlink transmissions by jointly optimizing the number of antennas at the base station, the number of served users, and the transmit power. Firstly, by considering the linear distortion due to hardware impairments, the resultant channel estimation error from both distortion and noise is analyzed, following which closed-form approximations for the average achievable uplink/downlink rates are derived. Then, a massive MIMO energy efficiency optimization problem considering hardware impairments is formulated. By applying the techniques of relaxation and change of variables, an alternative optimization with build-in bisection search (AO-BS) algorithm is proposed with the quasi-concavity of the transformed objective function theoretically proved. The performance of the proposed AO-BS algorithm is validated through numerical simulations, which shows fast convergence to near-optimal solutions. Compared with existing approaches, the proposed scheme improves the system energy efficiency greatly when the hardware impairments are considered. Furthermore, the system design guideline in terms of the number of antennas, the number of served users, and the transmit power is provided.
KW - alternative optimization
KW - channel estimation error
KW - energy efficiency
KW - hardware impairments
KW - linear distortion
KW - Massive multiple-input multiple-output
UR - http://www.scopus.com/inward/record.url?scp=85101488356&partnerID=8YFLogxK
U2 - 10.1109/TWC.2020.3028769
DO - 10.1109/TWC.2020.3028769
M3 - Article
SN - 1536-1276
VL - 20
SP - 843
EP - 857
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 2
M1 - 9226127
ER -