scholarly journals QoS Oriented Multiobjective Optimizer for Radio Resource Management of LTE-A Femtocells

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Ayesha Haider Ali ◽  
Muhammad Mohsin Nazir
Keyword(s):  
Resource Management ◽  
Radio Resource Management ◽  
Optimal Solution ◽  
Limited Resources ◽  
Radio Resource ◽  
Term Evolution ◽  
Data Rates ◽  
Transmission Opportunity

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.

An overview of downlink radio resource management for UTRAN long-term evolution

2009 ◽  
Vol 47 (7) ◽  
pp. 86-93 ◽  
Author(s):  
K.I. Pedersen ◽  
T.E. Kolding ◽  
F. Frederiksen ◽  
I.Z. Kovacs ◽  
D. Laselva ◽  
...  
Keyword(s):  
Resource Management ◽  
Radio Resource Management ◽  
Long Term Evolution ◽  
Radio Resource ◽  
Term Evolution

Radio Resource Management for Green 3GPP Long Term Evolution Cellular Networks: Review and Trade-offs

2013 ◽  
Vol 30 (3) ◽  
pp. 257 ◽  
Author(s):  
MustafaIsmael Salman ◽  
MuntadherQasim Abdulhasan ◽  
CheeKyun Ng ◽  
NorKamariah Noordin ◽  
Aduwati Sali ◽  
...  
Keyword(s):  
Resource Management ◽  
Cellular Networks ◽  
Radio Resource Management ◽  
Long Term Evolution ◽  
Radio Resource ◽  
Term Evolution ◽  
Trade Offs ◽  
3Gpp Long Term Evolution

A Survey of Radio Resource Management in Cognitive Radio Networks

2013 ◽  
pp. 264-289
Author(s):  
Chengshi Zhao ◽  
Wenping Li ◽  
Jing Li ◽  
Zheng Zhou ◽  
Kyungsup Kwak
Keyword(s):  
Cognitive Radio ◽  
Resource Management ◽  
Dynamic Spectrum Access ◽  
Radio Resource Management ◽  
Radio Spectrum ◽  
Radio Resource ◽  
Green Communications ◽  
Radio Resources ◽  
Adaptive Power

The framework of “green communications” has been proposed as a promising approach to address the issue of improving resource-efficiency and the energy-efficiency during the utilization of the radio spectrum. Cognitive Radio (CR), which performs radio resource sensing and adaptation, is an emerging technology that is up to the requests of green communications. However, CR networks impose serious challenges due to the fluctuating nature of the available radio resources corresponding to the diverse quality-of-service requirements of various applications. This chapter provides an overview of radio resource management in CR networks from several aspects, namely dynamic spectrum access, adaptive power control, time slot, and code scheduling. More specifically, the discussion focuses on the deployment of CR networks that do not require modification to existing networks. A brief overview of the radio resources in CR networks is provided. Then, three challenges to radio resource management are discussed.

scholarly journals Fair Optimization of Video Streaming Quality of Experience in LTE Networks Using Distributed Antenna Systems and Radio Resource Management

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Elias Yaacoub ◽  
Zaher Dawy
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
Radio Resource Management ◽  
Geometric Mean ◽  
Video Quality ◽  
Radio Resource ◽  
Distributed Antenna Systems ◽  
Distributed Antenna ◽  
Antenna Systems

Network quality of experience (QoE) metrics are proposed in order to capture the overall performance of radio resource management (RRM) algorithms in terms of video quality perceived by the end users. Metrics corresponding to average, geometric mean, and minimum QoE in the network are measured when Max C/I, proportional fair, and Max-Min RRM algorithms are implemented in the network. The objective is to ensure a fair QoE for all users in the network. In our study, we investigate both the uplink (UL) and downlink (DL) directions, and we consider the use of distributed antenna systems (DASs) to enhance the performance. The performance of the various RRM methods in terms of the proposed network QoE metrics is studied in scenarios with and without DAS deployments. Results show that a combination of DAS and fair RRM algorithms can lead to significant and fair QoE enhancements for all the users in the network.

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