Department of Information Technology, Faculty of Computers and Informatics, Zagazig University, Zagazig, Egypt.
Department of Information Technology, Faculty of Computers and Informatics, Cairo University, Giza, Egypt.
PLoS One. 2019 Apr 17;14(4):e0215334. doi: 10.1371/journal.pone.0215334. eCollection 2019.
Providing complete mobility along with minimizing the poor quality of service (QoS) is one of the highest essential challenges in mobile wireless networks. Handover prediction can overcome these challenges. In this paper, two novel prediction schemes are proposed. The first, depends on scanning the quality of all signals among mobile station and all nearby stations in the surrounding area, while the second one is based on a multi-criteria prediction decision using both the signal-to-noise ratio SNR value and station's bandwidth. Moreover, the prediction efficiency is improved by reducing the number of redundant/ unnecessary handovers. The proposed schemes are evaluated using different scenarios with several mobile stations' numbers, different WLAN access points, LTE-base station number & location, and random mobile station movement manner. The proposed schemes achieved a success rate of 99% with the different scenarios using LTE-WLAN architecture. The performance of the proposed prediction schemes outperformed the performance of the existing prediction schemes in terms of the accuracy percentage.
提供完全的移动性和最小化服务质量(QoS)差是移动无线网络的最高挑战之一。切换预测可以克服这些挑战。在本文中,提出了两种新的预测方案。第一种方案依赖于扫描移动站和周围区域中所有基站之间的所有信号质量,而第二种方案则基于使用信噪比(SNR)值和基站带宽的多标准预测决策。此外,通过减少冗余/不必要的切换数量来提高预测效率。使用不同的场景评估了所提出的方案,包括不同数量的移动站、不同的 WLAN 接入点、LTE 基站数量和位置以及随机移动站的移动方式。在所提出的使用 LTE-WLAN 架构的不同场景中,方案实现了 99%的成功率。在所提出的预测方案的性能方面,在准确性百分比方面优于现有的预测方案。