This paper proposes a QoE-driven LTE downlinkscheduling algorithm which is able to maximise the number of users per cell while maintaining an acceptable QoE for VoIP applications. The QoE-driven scheduling algorithm was implemented in LTE-Sim and its performance was compared to common LTE scheduling algorithms. The main difference between QoE-driven scheduling and existing scheduling mechanisms was prioritisation of users for resource allocation by taking into account their QoE requirements for VoIP applications. Preliminary results have shown that QoE-driven LTE downlink scheduling improved the cell capacity by 75% compared to MLWDF and 250% compared to PF and EXP-PF.
The purpose of this research is to fill the gap in the Technology Acceptance Model (TAM) in the context of multimedia-based learning in higher education. An additional variable - namely, subjective norm, has been added to TAM, and one of the main criticisms by the earlier researchers of it was that the model does not account for the human and social aspects of technology acceptance. The model has been empirically tested by the positivist paradigm of research using a sample size of 206 students in higher education in Kuwait, based on the convenience sampling method. A questionnaire survey through Google forms has been adopted to collect the quantitative data required for the study. The data was analyzed using the Structural Equation Modelling (SEM) technique. Nine hypotheses were postulated based on the extended TAM, among which six hypotheses were supported, and accordingly, the model has been fine-tuned. The most important finding of the study is that subjective norm has a significant and positive impact on both perceived ease of use and attitude towards the use of multimedia-based learning systems; however, the subjective norm has no direct significant influence on the intention to use. The hypothesis testing results have led to practical implications in the form of suggestions to technology managers in multimedia-based learning to enhance system use. The research has both theoretical and practical implications, and hence, will be useful to both academicians and practitioners.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.