Energy-Efficient Power Allocation for Underlay Cognitive Radio Systems

Sboui, Lokman; Rezki, Zouheir; Alouini, Mohamed‐Slim

doi:10.1109/tccn.2015.2488622

Cited by 38 publications

(19 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Turning off the radio frequency chains transmitted by sedentary antennas can save energy [18], [19]. Reference [20] proposed using a single antenna per user for point-to-point radio cognition. This improves EE in term of power allocation with average constraints.…”

Section: Related Workmentioning

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

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%

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

“…where P c denotes the on-board circuit power consumed by a UAV [21,22]. From (7), it can be observed that the total consumed power is determined by the UAV number, the on-board circuit power, and the average transmit power.…”

Section: System Model and Problem Formulation 21 System Modelmentioning

confidence: 99%

Altitude and number optimisation for UAV‐enabled wireless communications

Zhang

Zheng

et al. 2020

IET Communications

View full text Add to dashboard Cite

“…However, the reached solution is not entirely satisfactory as the lack of a closed-form solution does not allow to build sufficient insights into the problem. Recently, an explicit expression of the corresponding energy-efficient power allocation (EEPA) has been presented in [7] as P EE (γ) = 1 γ e 1+W ( γPc−1 e ) − 1 , where γ is the channel realization modulus squared and W is the main branch of W-Lambert function. Interestingly, the EE expression, in [7], presented new insights on the EE performance and particularly on the EE-SE relationship.…”

Section: A Siso Ee Power Controlmentioning

confidence: 99%

A New Relation Between Energy Efficiency and Spectral Efficiency in Wireless Communications Systems

Sboui

Rezki

Sultan

et al. 2019

IEEE Wireless Commun.

Self Cite

View full text Add to dashboard Cite

When designing wireless communication systems (WCS), spectral efficiency (SE) has been the main design performance metric. Recently, energy efficiency (EE) is attracting a huge interest due to the massive deployment of power limited WCS such as IoT devices, and stringent environmental concerns. For this reason, many works in the literature focused on optimizing the EE and highlighted the EE-SE relationship as a trade-off (meaning that increasing one decreases the other). In this article, after introducing the EE metric, we highlight a new perspective of the EE-SE relationship based on energy-efficient power control. In particular, we give insights about the EE-based performance of various transmission technologies and its impact on 5G future design. Via numerical results, we show that the corresponding power scheme allows an increase of both the SE as the EE with no trade-off. Finally, we present relevant open research problems.Index Terms-Energy efficiency, optimal power allocation, spectral efficiency.

show abstract

Energy-Efficient Power Allocation for Underlay Cognitive Radio Systems

Cited by 38 publications

References 33 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

Altitude and number optimisation for UAV‐enabled wireless communications

A New Relation Between Energy Efficiency and Spectral Efficiency in Wireless Communications Systems

Contact Info

Product

Resources

About