Frame-based QoS-aware multicast resource management model for optimizing multicast service in long term evoluation and beyond networks

• Main Author: Algharem, Mohammed Abdullah Ali
• Format: Thesis
• Language: English; English; English; English
• Published: 2020
• Subjects: T58.6-58.62 Management information systems
• Online Access: https://etd.uum.edu.my/8653/1/Depositpermission_not%20allow_s94166.pdf; https://etd.uum.edu.my/8653/2/s94166_01.pdf; https://etd.uum.edu.my/8653/3/s94166_02.pdf; https://etd.uum.edu.my/8653/4/s94166_references.docx; https://etd.uum.edu.my/8653/

Long Term Evolution (LTE) network offers high throughput with low latency, clearly making it the best choice for multicast services such as; news broadcast, video conferencing, weather reports and much more. In Conventional Multicast Scheme (CMS), data is concurrently transmitted to multicast users over the same channel using the lowest rate. As a result, the CMS performance is bind to the user with the lowest rate. Such scheme is unsatisfactory to users with stronger channels. Thus, an effective Multicast Resource Management (MRM) is needed to utilize all available bandwidth efficiently. This study aims to optimize the MRM policy by exploiting the multiuser diversity technique besides the multicast gain. A new Framed-based QoS-aware MRM (FQMRM) model with three main mechanisms was introduced. The first mechanism is used to enhance the CMS network by determining users who are expensive to cover. In this mechanism, the Opportunistic Multicast Scheme (OMS) is involved; thus, users with the best channel gain are firstly served, followed by cell edge users. The second and third mechanisms utilize the subgroup/layer formation by splitting multicast users into several subgroups. Each subgroup is served individually with a corresponding substream and rate in such a way that would maximize the multicast throughput. The FQ-MRM model uses dynamic programming with branch and bound technique to select the best subgroup configuration by considering video frame features and constraints, available resources, and queue status. These mechanisms were evaluated using LTE-Sim simulator. Simulation results show the throughput of the first, second and third mechanisms are 6.2%, 37%, and 18% respectively, which are better than the existing mechanisms in the literature. The results confirmed that the optimal subgroup configuration could be found within five subgroups only. Thus, the proposed mechanisms can improve multicast performance in LTE network.