Energy-Efficient Power Allocation With Individual and Sum Power Constraints

• Published in: IEEE transactions on wireless communications Vol. 17; no. 8; pp. 5353 - 5366
• Main Authors: He, Peter, Shan Zhang, Lian Zhao, Xuemin Shen
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computational complexity; Computer simulation; Energy efficiency; Energy efficiency (EE); exactness; geometric water-filling (GWF); Minimization; non-linear fractional optimization; Optimization; polynomial computational complexity; power allocation; Power efficiency; Power management; Resource management; Storage tanks; Throughput; Wireless communication
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2018.2842204

In this paper, we investigate the power allocation in a multi-user wireless system to maximize the energy efficiency, while meeting the power constrains of each individual user and the whole system. Specifically, a geometric ceiled-water-filling algorithm is proposed to solve this non-linear fractional optimization problem, which can compute exact solutions with a low degree of polynomial computational complexity. Optimality of the proposed algorithm is strictly proved with mathematical analysis. In addition, the proposed algorithm is further extended to the general case with the minimum system-level throughput constraint, considering the quality of service requirement. To the best of our knowledge, no prior algorithm in the open literature offered such optimal solutions to the target problems, with the merit of exactness and the efficiency. Simulation results demonstrate that the proposed power allocation algorithms can improve the energy efficiency by nearly 50%, compared with the conventional Dinkelbach's method with the same amount of computations.