학술논문

Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
Document Type
Periodical
Source
IEEE Access Access, IEEE. 8:203237-203251 2020
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Power demand
Transmitting antennas
Quality of service
Massive MIMO
Energy efficiency
Optimization
Antenna arrays
Energy efficiency (EE)
massive MIMO
quality of service (QoS)
base station (BS) transmit power
Language
ISSN
2169-3536
Abstract
In this paper, the power transmission and energy efficiency (EE) in downlink multi-cell massive multiple-input–multiple-output (MIMO) systems are investigated and optimized. Most of the existing works do not take into account different user’s quality of service (QoS) requirements. These models also depend on a fixed transmit power consumption, which cannot reflect the actual EE levels concerning QoS. Therefore, in this paper, a new base station (BS) transmit power adaptation is firstly introduced, termed the BSTPA method. The transmitted power is adapted to channel condition and user-level QoS including data rate requirement and maximum allowable outage probability to minimize the total BS radiated power. An analytical closed-form expression of the average BS transmit power adaptation is derived. Then, a corresponding iterative optimization algorithm is proposed to maximize the average EE per BS and obtain the optimal design parameters. The proposed optimization algorithm aims to globally achieve the optimal EE value with the optimal amount of data rate, the number of BS antennas, and users. Simulation results are demonstrated to verify our analytical findings. For a wide range of different design parameters, the results indicate that the proposed method obtains remarkably higher EE levels compared to the conventional scenario, particularly if per-antenna circuit power is very small. The optimization results show that the case with lower per-antenna circuit power can achieve about 4.5 times better EE gain than the case with higher per-antenna circuit power with 13.3% optimum data rate improvement.