Abstract
The ongoing development of mobile communication networks has led to an expressive growth in capacity demand, mainly due to video streaming services, which together with the Internet of Things sector represent a challenge for the mobile network operators. Video streaming is already responsible for most of the Internet traffic, and the real-time video calling services are becoming increasingly common. The use of strict quality of service parameters can lead to global resource starvation, where no user can be served with the resources available. In case of network congestion is important to prevent global resource starvation problem and also serve as many users as possible with a reasonable quality of service while still ensuring a minimum of connectivity to other users. Considering this problem, this article presents a new channel-aware downlink packet scheduler for Long Term Evolution networks that aims to increase the number of satisfied real-time video streaming users. The performance evaluation was done through computer simulations, using peak signal-to-noise ratio (PSNR) to compare the quality delivered by competing algorithms, and the number of users who are given enough resources to play video with quality. The results indicate that the proposed method outperforms the commonly-used algorithms considering the number of satisfied users and average video PSNR, mainly under moderate-to-heavy traffic load conditions.
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Pedroso, C.M., da Silva, C.A.G., Barbosa Junior, J.A. et al. A Low-Complexity Scheduler to Improve the Number of Satisfied Video Streaming Users in LTE. Wireless Pers Commun 109, 1121–1132 (2019). https://doi.org/10.1007/s11277-019-06606-5
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DOI: https://doi.org/10.1007/s11277-019-06606-5