Power allocation for massive MIMO: Impact of power amplifier efficiency

Ye, Guo; Tang, Junlin; Wu, Gang; Li, Shaoqian

doi:10.1109/iccchina.2015.7448697

Cited by 6 publications

(7 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reduced low-complexity energy and good network performance in single-cell massive MIMO systems were achieved by using a joint several-antenna selection and power optimization algorithm in [11]. The author in [17] proposed to improve EE while achieving high spectral efficiency in massive MIMO systems by using a power amplifier and a power allocation algorithm based on zero-forcing. From the existing works, the study focuses on an EE optimization problem for a DL single-cell massive MIMO system with perfect CSI.…”

Section: Related Workmentioning

confidence: 99%

“…The non-convex optimization problem k in (17), can be transformed into a convex optimization. The optimal solution of user association can be obtained by applying the KKT conditions to set the partial derivative ∂ k (γ ) ∂k j = 1 when a user association X j,k = 1, as j k = arg max j ln j,k − γ j (24) The proposed EELCA can guarantee the optimal data rate of UEs R j,k association with optimal a number of antennas of BSs j = 1, .…”

Section: E Constrained Joint User Associationmentioning

confidence: 99%

See 1 more Smart Citation

Energy-Efficient Power Allocation and Joint User Association in Multiuser-Downlink Massive MIMO System

et al. 2020

View full text Add to dashboard Cite

Singular value decomposition is highly essential to achieve a higher performance in signal processing using massive multiple-input multiple-output (MIMO) systems. This paper aims to provide a solution to control power allocation problem identified as an essential metric in a massive MIMO system that maximizes energy efficiency (EE). The network performance was evaluated by measuring circuit power consumption to maximize EE. The computational efficiency to maximize EE power allocation is very important to fifth generation networks (5G). The study aims to maximize the non-convex EE in a downlink (DL) massive MIMO system using a proposed energy-efficient low-complexity algorithm (EELCA) that guarantees optimal power allocation solution based on Newton's methods and joint user's association based on the Lagrange's decomposition method. An optimal power allocation solution in closed form to decrease the complexity of the power subject to both the maximum power and minimum data rate constrained systems was derived. Then, the unconstrained EE power allocation to solve the unconstrained optimal power was used to select the optimal power allocation by computing a root of the first derivative of the EE based on differentiating the instantaneous power allocation to maximize EE was formulated. Simulation results showed that the proposed EELCA with a total transmitted power allocation provided maximum EE for a large number of antennas at the base station (BS), Generally, non-linear schemes outperformed linear schemes. Finally, the large cost of circuit power consumption increased at the BS due to the large loss of radio frequency (RF) chains at every antenna when the signals were transmitted to all users. The maximum EE = 5.9 Mbits/joule when the number of distributed users, K = 33, with (p c , M) = (1000mW, 200). The proposed low complexity algorithm provides the better result EE based on a training channel for a number of distributed users.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: E Constrained Joint User Associationmentioning

confidence: 99%

Energy-Efficient Power Allocation and Joint User Association in Multiuser-Downlink Massive MIMO System

et al. 2020

View full text Add to dashboard Cite

show abstract

“…As the most power-consuming component of the RF transceiver, the PA plays an important role, particularly in terms of the system coverage and overall power efficiency [60]. With benefits of multi-antenna array, a large coverage can be achieved by using PA with moderate output power.…”

Section: Power Amplifiermentioning

confidence: 99%

mmWave communications for 5G: implementation challenges and advances

Wang

Niu

et al. 2018

Sci. China Inf. Sci.

View full text Add to dashboard Cite

An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications SCIENCE CHINA Information Sciences 59, 081301 (2016); An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications SCIENTIA SINICA Informationis 46, 3 (2016); 6-100 GHz research progress and challenges from a channel perspective for fifth generation (5G) and future wireless communication SCIENCE CHINA Information Sciences 60, 080301 (2017); SCIENCE CHINA Information Sciences

show abstract

“…Moreover, massive MIMO systems exploit a huge number of antenna arrays at the BS to provide a sufficient data rate to many users. Massive MIMO systems are able to provide higher EE than single antenna when only take the account transmit power of users [1], and [2]. Energy consumption that reduces transmit power is due to the direct impact of the carbon emission problem of BS; therefore, it is necessary to reduce the high level of energy consumption.…”

Section: Introductionmentioning

confidence: 99%

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

Salh¹,

Audah²,

Shah³

et al. 2018

IJET

View full text Add to dashboard Cite

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.

show abstract

Power allocation for massive MIMO: Impact of power amplifier efficiency

Cited by 6 publications

References 19 publications

Energy-Efficient Power Allocation and Joint User Association in Multiuser-Downlink Massive MIMO System

Energy-Efficient Power Allocation and Joint User Association in Multiuser-Downlink Massive MIMO System

mmWave communications for 5G: implementation challenges and advances

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

Contact Info

Product

Resources

About