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Mobile Information Systems - Volume 2016 2016, Article ID 7964359, 13 pages -

Research ArticleDepartment of Computer Science, Lahore College for Women University, Jail Road, Lahore 54000, Pakistan

Received 8 March 2016; Accepted 16 June 2016

Academic Editor: Pedro M. Ruiz

Copyright © 2016 Ayesha Haider Ali and Muhammad Mohsin Nazir. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The future wireless networks support multimedia applications and require ensuring quality of the services they provide. With increasing number of users, the radio resource is becoming scarce. Therefore, how should the demands for higher data rates with limited resources be met for Long Term Evolution-Advanced LTE-A is turning out to be a vital issue. In this research paper we have proposed an innovative approach for Radio Resource Management RRM that makes use of the evolutionary multiobjective optimization MOO technique for Quality of Service QoS facilitation and embeds it with the modern techniques for RRM. We have proposed a novel Multiobjective Optimizer MOZ that selects an optimal solution out of a Pareto optimal PO set in accordance with the users QoS requirements. We then elaborate the scheduling process and prove through performance evaluation that use of MOO can provide potential solutions for solving the problems for resource allocation in the advancement of LTE-A networks. Simulations are carried out using LTE-Sim simulator, and the results reveal that MOZ outperforms the reference algorithm in terms of throughput guarantees, delay bounds, and reduced packet loss. Additionally, it is capable of achieving higher throughput and lower delay by giving equal transmission opportunity to all users and achieves 100% accuracy in terms of selecting optimal solution.

Author: Ayesha Haider Ali and Muhammad Mohsin Nazir

Source: https://www.hindawi.com/


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