Generalized water-filling for sum power minimization with peak power constraints

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 proposed a generalized water-filling approach to solve the power allocation problem to minimize sum power while meet 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 constrains. The more stringent constrains can be used for advanced communications, such as those under cognitive radio (CR). The proposed algorithms with the generalized approach possess distinguished features. Exact closed-form solutions are proposed to the target problem. Since some of the variables have their corresponding geometric interpretation, the proposed algorithms provide more insights to the problems and could be used to efficiently solve the family of the sum power minimization problems. Optimality of the proposed algorithms is strictly proved. Numerical results illustrate the steps and demonstrate efficiency of the proposed algorithms. To the best of the authors´ knowledge, there is no similar work reported in the open literature.