Solving a Class of Sum Power Minimization Problems by Generalized Water-Filling

• Published in: IEEE transactions on wireless communications Vol. 14; no. 12; pp. 6792 - 6804
• Main Authors: He, Peter, Lian Zhao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Allocations; Derivatives; Linear programming; Mathematical analysis; Mathematical models; maximum sum data rate; Minimization; minimum sum power; Optimization; Resource management; Throughput; Water-filling; Wireless communication; maximum sum data rate; QoS; Water-filling; channel capacity; optimal radio resource management (RRM); minimum sum power; optimization methods
• DOI: 10.1109/TWC.2015.2459714
• ISSN: 1536-1276

Radio resource management (RRM) plays an important role in wireless communication systems, especially in more advanced systems with more constraint conditions. In this paper, we first propose a generalized water-filling approach to solve the power allocation problem of minimizing sum power while meeting the target sum rate constraint with weights. Based on this sum power objective function, we extend the proposed method to more complicated RRM problems with more stringent constraints. The proposed algorithms with this generalized approach possess several distinguished features. They provide exact optimal solutions based on non-derivative methods, as the implementation of the proposed algorithms invokes neither the derivative nor the gradient. With geometric interpretation, the proposed algorithms provide more insights into and intuitions of the problems and could be used to efficiently solve a family of the sum power minimization problems. Optimality of the proposed algorithms is strictly proved. Numerical results that illustrate the steps and demonstrate efficiency of the proposed algorithms are presented.