Please use this identifier to cite or link to this item: http://repository.aaup.edu/jspui/handle/123456789/1438
Title: Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
Authors: Khodamoradi, Vahid $Other$Other
Sali, Aduwati $Other$Other
Messadi, Oussama $Other$Other
Salah, Asem $AAUP$Palestinian
Al-Wani, Mohanad$Other$Other
Mohd Ali, Borhanuddin $Other$Other
Raja Abdullah, Raja Syamsul Azmir $Other$Other
Keywords: Energy ef ciency (EE),
massive MIMO
quality of service (QoS),
base station (BS) transmit power
Issue Date: 11-Nov-2020
Publisher: IEEE Access
Citation: Khodamoradi, Vahid, Aduwati Sali, Oussama Messadi, Asem A. Salah, Mohanad M. Al-Wani, Borhanuddin Mohd Ali, and Raja Syamsul Azmir Raja Abdullah. "Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems." IEEE Access 8 (2020): 203237-203251.
Series/Report no.: IEEE Access 8 (2020);203237-203251
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.
URI: http://repository.aaup.edu/jspui/handle/123456789/1438
ISSN: 2169-3536
Appears in Collections:Faculty & Staff Scientific Research publications



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