Transmit Power Allocation and Energy Efficiency Optimization of Distributed MIMO

2020 ◽  
pp. 89-107
Author(s):  
Xiaohu You ◽  
Dongming Wang ◽  
Jiangzhou Wang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Transmit Power ◽  
Efficiency Optimization

Energy Efficiency Optimization: Joint Antenna-Subcarrier-Power Allocation in OFDM-DASs

2016 ◽  
Vol 15 (11) ◽  
pp. 7470-7483 ◽  
Author(s):  
Xiuhua Li ◽  
Xin Ge ◽  
Xiaofei Wang ◽  
Julian Cheng ◽  
Victor C. M. Leung
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Efficiency Optimization

scholarly journals Efficient Multiway Relaying for Data Sharing in Energy Harvesting Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Moslem Noori ◽  
Masoud Ardakani
Keyword(s):  
Energy Efficiency ◽  
Energy Harvesting ◽  
Power Allocation ◽  
Data Sharing ◽  
Data Aggregation ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Amplify And Forward ◽  
Transmit Power ◽  
Achievable Data Rate

In a wireless sensor network (WSN), sensors often need to share their measurements for applications like distributed estimation and detection or data aggregation. Here, we suggest using multiway relaying (MWR) for data sharing between energy harvesting sensors that cannot directly communicate with each other. We first start by studying the achievable data rate of amplify-and-forward (AF) MWR for energy harvesting sensors. Then, we show that, by backing off the transmit power at the sensors, not only better energy efficiency and longer lifetime are achieved, but also the data sharing rate increases. Based on this result, we further improve the performance of AF MWR in the assumed WSN by smartly adjusting the transmit power at the sensors. Our power allocation is devised in a way to improve the energy efficiency of MWR and increase the sum rate of data sharing between the sensors over the network lifetime. Simulation results are presented to verify the enhancement achieved by using our proposed power allocation technique.

scholarly journals Power Allocation for Energy Efficiency Optimization in Multi-User mmWave-NOMA System With Hybrid Precoding

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 109083-109093 ◽  
Author(s):  
Xiangbin Yu ◽  
Fangcheng Xu ◽  
Kai Yu ◽  
Xiaoyu Dang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Efficiency Optimization ◽  
Hybrid Precoding

scholarly journals Maximizing Energy Efficiency in Downlink Massive MIMO Systems by Full-complexity Reduced Zero-forcing Beamforming

2018 ◽  
Vol 7 (4.1) ◽  
pp. 33
Author(s):  
Adeeb Salh ◽  
Lukman Audah ◽  
Nor. S. M. Shah ◽  
Shipun. A. Hamzah
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Power Allocation ◽  
Mimo System ◽  
Renewable Energy Sources ◽  
Base Station ◽  
Zero Forcing ◽  
Transmit Power ◽  
Battery Capacity ◽  
Circuit Power

Energy efficiency (EE) is one of the key design goals for fifth-generation (5G) cellular networks due to the intermittent properties of renewable energy sources and limited battery capacity. In this paper, we analyze the EE of downlink (DL) massive multi-user multiple-input multiple-output (MIMO) system based on circuit power consumption for the transmit antenna configuration. We designed full complexity reduced zero-forcing (ZF) beamforming to cancel out interbeam interference when the number of antennas   and minimized the power consumption model, when formulating the power allocation optimization problem with the Lagrange duality method, in order to maximize EE. Simulation results revealed that the EE in the base station (BS) could be improved when the number of radio frequency (RF) chains was proportional to the optimal transmit power allocation and when the consumption circuit power was comparable to the transmit power.  

Sign in / Sign up

Export Citation Format

Share Document