The problem of weighted throughput maximization is generally non convex and computationally intense. A solution, known as MLFP-based power allocation or MAPEL algorithm, transforms the problem into a multiplicative linear fractional programming problem and then uses a method based on polyblock outer approximation. In this paper, we are going to use some techniques for reducing MAPEL computational time, in particular regarding the minimum rate constraint in the optimization problem. Furthermore, we are introducing, in the optimization procedure, the water filling principle in order to respect a maximum available power per user when the allocation has to be performed in more resource blocks.

Application of the Water Filling Algorithm to the Sum Rate Problem with Minimum Rate and Power Constraint

O. Elgarhy;L. Reggiani
2018-01-01

Abstract

The problem of weighted throughput maximization is generally non convex and computationally intense. A solution, known as MLFP-based power allocation or MAPEL algorithm, transforms the problem into a multiplicative linear fractional programming problem and then uses a method based on polyblock outer approximation. In this paper, we are going to use some techniques for reducing MAPEL computational time, in particular regarding the minimum rate constraint in the optimization problem. Furthermore, we are introducing, in the optimization procedure, the water filling principle in order to respect a maximum available power per user when the allocation has to be performed in more resource blocks.
Proceedings of Advances in Wireless and Optical Communications 2018
978-1-5386-5558-0
Maximum Throughput, MAPEL, Optimal Power Allocation, Water Filling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1085474
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