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2020-12-14
Goudos, S. K., Diamantoulakis, P. D., Boursianis, A. D., Papanikolaou, V. K., Karagiannidis, G. K..  2020.  Joint User Association and Power Allocation Using Swarm Intelligence Algorithms in Non-Orthogonal Multiple Access Networks. 2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST). :1–4.
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.
2018-08-23
Ming, X., Shu, T., Xianzhong, X..  2017.  An energy-efficient wireless image transmission method based on adaptive block compressive sensing and softcast. 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). :712–717.

With the rapid and radical evolution of information and communication technology, energy consumption for wireless communication is growing at a staggering rate, especially for wireless multimedia communication. Recently, reducing energy consumption in wireless multimedia communication has attracted increasing attention. In this paper, we propose an energy-efficient wireless image transmission scheme based on adaptive block compressive sensing (ABCS) and SoftCast, which is called ABCS-SoftCast. In ABCS-SoftCast, the compression distortion and transmission distortion are considered in a joint manner, and the energy-distortion model is formulated for each image block. Then, the sampling rate (SR) and power allocation factors of each image block are optimized simultaneously. Comparing with conventional SoftCast scheme, experimental results demonstrate that the energy consumption can be greatly reduced even when the receiving image qualities are approximately the same.