Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/630633
Title: Energy Efficiency Optimization of 5G Radio Frequency Chain Systems
Authors: Ran Zi;Xiaohu Ge;John Thompson;Cheng-Xiang Wang;Haichao Wang;Tao Han
subject: cost efficiency|5G wireless communication systems|baseband processing|radio frequency chains|Energy efficiency
Year: 2016
Publisher: IEEE
Abstract: With the massive multi-input multi-output (MIMO) antennas technology adopted for the fifth generation (5G) wireless communication systems, a large number of radio frequency (RF) chains have to be employed for RF circuits. However, a large number of RF chains not only increase the cost of RF circuits but also consume additional energy in 5G wireless communication systems. In this paper, we investigate energy and cost efficiency optimization solutions for 5G wireless communication systems with a large number of antennas and RF chains. An energy efficiency optimization problem is formulated for 5G wireless communication systems using massive MIMO antennas and millimeter wave technology. Considering the nonconcave feature of the objective function, a suboptimal iterative algorithm, i.e., the energy efficient hybrid precoding (EEHP) algorithm is developed for maximizing the energy efficiency of 5G wireless communication systems. To reduce the cost of RF circuits, the energy efficient hybrid precoding with the minimum number of RF chains (EEHP-MRFC) algorithm is also proposed. Moreover, the critical number of antennas searching (CNAS) and user equipment number optimization (UENO) algorithms are further developed to optimize the energy efficiency of 5G wireless communication systems by the number of transmit antennas and UEs. Compared with the maximum energy efficiency of conventional zero-forcing (ZF) precoding algorithm, numerical results indicate that the maximum energy efficiency of the proposed EEHP and EEHP-MRFC algorithms are improved by 220% and 171%, respectively.
Description: 
URI: http://localhost/handle/Hannan/171182
http://localhost/handle/Hannan/630633
ISSN: 0733-8716
volume: 34
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7440793.pdf2.04 MBAdobe PDFThumbnail
Preview File
Title: Energy Efficiency Optimization of 5G Radio Frequency Chain Systems
Authors: Ran Zi;Xiaohu Ge;John Thompson;Cheng-Xiang Wang;Haichao Wang;Tao Han
subject: cost efficiency|5G wireless communication systems|baseband processing|radio frequency chains|Energy efficiency
Year: 2016
Publisher: IEEE
Abstract: With the massive multi-input multi-output (MIMO) antennas technology adopted for the fifth generation (5G) wireless communication systems, a large number of radio frequency (RF) chains have to be employed for RF circuits. However, a large number of RF chains not only increase the cost of RF circuits but also consume additional energy in 5G wireless communication systems. In this paper, we investigate energy and cost efficiency optimization solutions for 5G wireless communication systems with a large number of antennas and RF chains. An energy efficiency optimization problem is formulated for 5G wireless communication systems using massive MIMO antennas and millimeter wave technology. Considering the nonconcave feature of the objective function, a suboptimal iterative algorithm, i.e., the energy efficient hybrid precoding (EEHP) algorithm is developed for maximizing the energy efficiency of 5G wireless communication systems. To reduce the cost of RF circuits, the energy efficient hybrid precoding with the minimum number of RF chains (EEHP-MRFC) algorithm is also proposed. Moreover, the critical number of antennas searching (CNAS) and user equipment number optimization (UENO) algorithms are further developed to optimize the energy efficiency of 5G wireless communication systems by the number of transmit antennas and UEs. Compared with the maximum energy efficiency of conventional zero-forcing (ZF) precoding algorithm, numerical results indicate that the maximum energy efficiency of the proposed EEHP and EEHP-MRFC algorithms are improved by 220% and 171%, respectively.
Description: 
URI: http://localhost/handle/Hannan/171182
http://localhost/handle/Hannan/630633
ISSN: 0733-8716
volume: 34
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7440793.pdf2.04 MBAdobe PDFThumbnail
Preview File
Title: Energy Efficiency Optimization of 5G Radio Frequency Chain Systems
Authors: Ran Zi;Xiaohu Ge;John Thompson;Cheng-Xiang Wang;Haichao Wang;Tao Han
subject: cost efficiency|5G wireless communication systems|baseband processing|radio frequency chains|Energy efficiency
Year: 2016
Publisher: IEEE
Abstract: With the massive multi-input multi-output (MIMO) antennas technology adopted for the fifth generation (5G) wireless communication systems, a large number of radio frequency (RF) chains have to be employed for RF circuits. However, a large number of RF chains not only increase the cost of RF circuits but also consume additional energy in 5G wireless communication systems. In this paper, we investigate energy and cost efficiency optimization solutions for 5G wireless communication systems with a large number of antennas and RF chains. An energy efficiency optimization problem is formulated for 5G wireless communication systems using massive MIMO antennas and millimeter wave technology. Considering the nonconcave feature of the objective function, a suboptimal iterative algorithm, i.e., the energy efficient hybrid precoding (EEHP) algorithm is developed for maximizing the energy efficiency of 5G wireless communication systems. To reduce the cost of RF circuits, the energy efficient hybrid precoding with the minimum number of RF chains (EEHP-MRFC) algorithm is also proposed. Moreover, the critical number of antennas searching (CNAS) and user equipment number optimization (UENO) algorithms are further developed to optimize the energy efficiency of 5G wireless communication systems by the number of transmit antennas and UEs. Compared with the maximum energy efficiency of conventional zero-forcing (ZF) precoding algorithm, numerical results indicate that the maximum energy efficiency of the proposed EEHP and EEHP-MRFC algorithms are improved by 220% and 171%, respectively.
Description: 
URI: http://localhost/handle/Hannan/171182
http://localhost/handle/Hannan/630633
ISSN: 0733-8716
volume: 34
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7440793.pdf2.04 MBAdobe PDFThumbnail
Preview File