| Title | Joint User Association and Power Allocation Using Swarm Intelligence Algorithms in Non-Orthogonal Multiple Access Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Goudos, S. K., Diamantoulakis, P. D., Boursianis, A. D., Papanikolaou, V. K., Karagiannidis, G. K. |
| Conference Name | 2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST) |
| Keywords | 5G, composability, compositionality, Evolutionary algorithms, Grey Wolf optimizer, Interference, joint user association-power allocation, multi-access systems, multiple base stations, NOMA, NOMA networks, Non-Orthogonal Multiple Access (NOMA), nonorthogonal multiple access networks, orthogonal clusters, particle swarm optimisation, particle swarm optimization, physical resource block allocation, power allocation, PSO, pubcrawl, Receivers, resource allocation, Resource management, Signal to noise ratio, Silicon carbide, swarm intelligence, swarm intelligence algorithms, user association, user grouping procedure, weighted sum rate maximization |
| Abstract | In this paper, we address the problem of joint user association and power allocation for non-orthogonal multiple access (NOMA) networks with multiple base stations (BSs). A user grouping procedure into orthogonal clusters, as well as an allocation of different physical resource blocks (PRBs) is considered. The problem of interest is mathematically described using the maximization of the weighted sum rate. We apply two different swarm intelligence algorithms, namely, the recently introduced Grey Wolf Optimizer (GWO), and the popular Particle Swarm Optimization (PSO), in order to solve this problem. Numerical results demonstrate that the above-described problem can be satisfactorily addressed by both algorithms. |
| DOI | 10.1109/MOCAST49295.2020.9200248 |
| Citation Key | goudos_joint_2020 |
Joint User Association and Power Allocation Using Swarm Intelligence Algorithms in Non-Orthogonal Multiple Access Networks