scholarly journals Smart Radio Resource Management for Content Delivery Services in 5G and Beyond Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Dominik Neznik ◽  
Lubomir Dobos ◽  
Jan Papaj
Keyword(s):  
Game Theory ◽  
Fuzzy Logic ◽  
Resource Management ◽  
Radio Resource Management ◽  
Content Delivery ◽  
Spectrum Allocation ◽  
Radio Resource ◽  
Advantages And Disadvantages ◽  
Delivery Services

In 5G networks, the spectrum allocation techniques play a very important part of the quality of content delivery services. The processes of channelling and device selection are important in the 5G technology and beyond with many access devices in networks to improve the quality of services. In this paper, we propose a method based on Fuzzy Logic, Game Theory, and Smart Method (which is a combination of Fuzzy Logic and Game Theory). These methods are suitable to improve the speed and quality of links of data routing in networks. The paper shows that effective spectrum allocation to devices is not an option but a requirement in a huge data flow environment of the wireless communications, if one wants to ensure acceptable speed and quality of the connection and to provide adequate quality of the services. Each of the selected methods for radio resource management has some advantages and disadvantages in the evaluation of results. The paper describes the process of channel allocation with different methods for IEEE 802.11xx networks that are in the focus of our research in the sphere of wireless communication. Companies use cloud computing to provide services and to share information, but there needs to be some radio resource management to effectively use the services in the wireless mobile environment because the number of different types of devices being connected to the wireless networks to create smart homes and smart cities is growing.

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.

Interval type-2 fuzzy logic based radio resource management in multi-radio WSNs

2018 ◽  
Vol 35 (2) ◽  
pp. 2525-2536 ◽  
Author(s):  
Wei Peng ◽  
Dongyan Chen ◽  
Wenhui Sun ◽  
Chengdong Li ◽  
Guiqing Zhang
Keyword(s):  
Fuzzy Logic ◽  
Resource Management ◽  
Radio Resource Management ◽  
Radio Resource ◽  
Interval Type

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.

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.

Game Theory Based Radio Resource Management Algorithm for Packet Access Cellular Networks

2017 ◽  
Vol 9 (1) ◽  
pp. 19-32
Author(s):  
Mihály Varga ◽  
Zsolt Alfréd Polgár
Keyword(s):  
Game Theory ◽  
Resource Management ◽  
Radio Resource Management ◽  
Low Complexity ◽  
Radio Resource ◽  
Average Delay ◽  
Management Algorithm ◽  
High Spectral Efficiency ◽  
Suboptimal Solution ◽  
Multidimensional Optimization

AbstractThe goal of Radio Resource Management (RRM) mechanisms is to allocate the transmission resources to the users such that the transmission requests are satisfied while several constraints are fulfilled. These constraints refer to low complexity and power consumption and high spectral efficiency and can be met by multidimensional optimization. This paper proposes a Game Theory (GT) based suboptimal solution to this multidimensional optimization problem. The results obtained by computer simulations show that the proposed RRM algorithm brings significant improvement in what concerns the average delay and the throughput, compared to other RRM algorithms, at the expense of somewhat increased complexity.

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