This is the code package related to the follow scientific article: Andrea Pizzo, Alessio Zappone and Luca Sanguinetti, "Solving Energy Efficiency Problems through Polynomial Optimization Theory," IEEE Signal Processing Letters, Submitted to. The package contains a simulation environment, based on Matlab, that reproduces all the numerical results and figures in the article. We encourage you to also perform reproducible research!
This work introduces the framework of polynomial optimization theory to solve fractional polynomial programs (FPP) and shows how it can be applied to energy-efficiency maximization in communications. Unlike other widely used optimization frameworks, the proposed one applies to a larger class of FPP, not necessarily defined by an objective given by the ratio of concave and convex functions. In particular, we provide an iterative algorithm that is provably convergent and enjoys asymptotic optimality properties. Numerical results are used to validate its accuracy in the non-asymptotic regime. To this end, we consider a cellular network and maximize the energy efficiency with respect to the number of antennas and user equipments.
The article contains 2 simulation figures, Fig. 1 and Fig. 2 as they appear in the article. These are generated by the Matlab scripts Fig1main.m and Fig2main.m, respectively. The package contains two additional Matlab scripts (that contain the system model parameters) and one function (auxiliary to Fig. 2) which are called by the main scripts: Fig1main.m and Fig2main.m. See each file for further documentation.
This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.