Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This code package is related to the following scientific article:
Alessio Zappone, Bho Matthiesen, and Eduard Jorswieck, "Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems," IEEE Transactions on Signal Processing, vol. 65, no. 4, pp. 1026-1041 Feb. 2017.
This paper addresses the problem of resource allocation for systems in which a primary and a secondary link share the available spectrum by an underlay or overlay approach. After observing that such a scenario models both cognitive radio and D2D communications, we formulate the problem as the maximization of the secondary energy efficiency subject to a minimum rate requirement for the primary user. This leads to challenging nonconvex, fractional problems. In the underlay scenario, we obtain the global solution by means of a suitable reformulation. In the overlay scenario, two algorithms are proposed. The first one yields a resource allocation fulfilling the first-order optimality conditions of the resource allocation problem, by solving a sequence of easier fractional programs. The second one enjoys a weaker optimality claim, but an even lower computational complexity. Numerical results demonstrate the merits of the proposed algorithms both in terms of energy-efficient performance and complexity, also showing that the two proposed algorithms for the overlay scenario perform very similarly, despite the different complexity.
We have decided to relase this code although it is in no shape to do so. This is due to several requests we have received since the first publication of this article. It is provided as is, without any documentation or support.
The overlay code should be located in the root folder and mpi/. If I recall correctly, we have used the bcMPI toolbox and Open MPI to run it. The start script is mpi/manager.m. The underlay code should be easier to run and is located in underlay/. In addition, the CVX toolbox is required, possibly with a professional license that is free of charge for academic users. Good luck!
The work of A. Zappone was supported by the German Research Foundation, Deutsche Forschungsgemeinschaft (DFG), under grant ZA 747/1-3.
The work of E. Jorswieck and B. Matthiesen was supported in part by the DFG in the Collaborative Research Center 912 "Highly Adaptive Energy-Efficient Computing".
This program 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.