scholarly journals Resource Allocation Schemes for 5G Network: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6588
Author(s):  
Muhammad Ayoub Kamal ◽  
Hafiz Wahab Raza ◽  
Muhammad Mansoor Alam ◽  
Mazliham Mohd Su’ud ◽  
Aznida binti Abu Bakar Sajak
Keyword(s):  
Resource Allocation ◽  
Network Performance ◽  
Resource Distribution ◽  
Interference Management ◽  
Small Cells ◽  
Current Evidence ◽  
Future Research ◽  
Layer Model ◽  
Research Areas ◽  
Resource Allocation Schemes

Fifth-generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, lower power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising device-to-device networks, macro-cells, and different categories of small cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need for cellular service and the limited resources to provide it, capably handling network traffic and operation has become a problem of resource distribution. One of the utmost serious problems is to alleviate the jamming in the network in support of having a better QoS. However, although a limited number of review papers have been written on resource distribution, no review papers have been written specifically on 5G resource allocation. Hence, this article analyzes the issue of resource allocation by classifying the various resource allocation schemes in 5G that have been reported in the literature and assessing their ability to enhance service quality. This survey bases its discussion on the metrics that are used to evaluate network performance. After consideration of the current evidence on resource allocation methods in 5G, the review hopes to empower scholars by suggesting future research areas on which to focus.

scholarly journals Resource Allocation Schemes For 5G Network: A Systematic Review

2021 ◽  
Author(s):  
Muhammad Ayoub Kamal ◽  
Hafiz Wahab Raza ◽  
Muhammad Mansoor Alam ◽  
M.S. Mazliham
Keyword(s):  
Resource Allocation ◽  
Resource Distribution ◽  
Interference Management ◽  
Small Cells ◽  
Layer Model ◽  
Research Areas ◽  
Fifth Generation ◽  
Data Rates ◽  
5G Network ◽  
Resource Allocation Schemes

Fifth Generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising of device-to-device networks, macro-cells, and dissimilar categories of small-cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need and the lack of resources, the resource distribution problem desires to be focused capably to accomplish the traffic and to enhance network working. One of the utmost serious problems is to alleviate the jamming from the network in support of having a better QoS. However, there are limited review papers written on resource distribution, there is no particularize and organized review carry out in 5G resource allocation. Hence, this article covers and evaluates the argument using a classification of existing developing resource allocation schemes in 5G thoroughly by classifying the schemes to enhance the service quality. This survey comprises the discussion based on metrics used to evaluate the performance. It would also permit ahead beyond evidence on resource allocation methods in 5G and empowers the scholars to meet the present research areas to focus on.

scholarly journals A survey on computation resource allocation in IoT enabled vehicular edge computing

2021 ◽  
Author(s):  
Naren ◽  
Abhishek Kumar Gaurav ◽  
Nishad Sahu ◽  
Abhinash Prasad Dash ◽  
G. S. S. Chalapathi ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Mathematical Models ◽  
Network Performance ◽  
Edge Computing ◽  
High Rate ◽  
Maximum Efficiency ◽  
Future Research ◽  
The Future ◽  
Future Research Directions ◽  
Resource Allocation Schemes

AbstractThe number of vehicles is increasing at a very high rate throughout the globe. It reached 1 billion in 2010, in 2020 it was around 1.5 billion and experts say this could reach up to 2–2.5 billion by 2050. A large part of these vehicles will be electrically driven and connected to a vehicular network. Rapid advancements in vehicular technology and communications have led to the evolution of vehicular edge computing (VEC). Computation resource allocation is a vehicular network’s primary operations as vehicles have limited onboard computation. Different resource allocation schemes in VEC operate in different environments such as cloud computing, artificial intelligence, blockchain, software defined networks and require specific network performance characteristics for their operations to achieve maximum efficiency. At present, researchers have proposed numerous computation resource allocation schemes which optimize parameters such as power consumption, network stability, quality of service (QoS), etc. These schemes are based on widely used optimization and mathematical models such as the Markov process, Shannon’s law, etc. So, there is a need to present an organized overview of these schemes to help in the future research of the same. In this paper, we classify state-of-the-art computation resource allocation schemes based on three criteria: (1) Their optimization goal, (2) Mathematical models/algorithms used, and (3) Major technologies involved. We also identify and discuss current issues in computation resource allocation in VEC and mention the future research directions.

scholarly journals The Influence of Innovation in Tangible and Intangible Resource Allocation: A Qualitative Multi Case Study

2020 ◽  
Vol 12 (12) ◽  
pp. 4989
Author(s):  
Rui Silva ◽  
Cidália Oliveira
Keyword(s):  
Resource Allocation ◽  
Organizational Performance ◽  
Balanced Scorecard ◽  
Dynamic Capabilities ◽  
Business Processes ◽  
Research Area ◽  
Future Research ◽  
Resource Monitoring ◽  
Knowledge Resources ◽  
Research Areas

Considering the current turbulent macroeconomic environment, the aim of this research is to explore the influence of innovation in tangible and intangible resource allocation. The literature underlines that organizations are facing a revolution in their business processes. As such, there is a need to understand the value of knowledge resources and to identify ways to manage them. This paper explores the field of resource allocation, namely dynamic capabilities, and highlights the importance of monitoring intangible resources. This research has three specific contributions. The first contribution provides a comprehensive picture of what has occurred in the field of tangible and intangible resource allocation, such as intellectual capital and its importance towards organizational performance. Secondly, it offers evidence about the actual need for performance measurement tools that foster intangible resource monitoring. Organizations devote special attention to market demands which consequently lead managers to adapt their strategies in areas concerning resource allocation. Given this importance, this research, comprising major innovative organizations in Portugal from diverse activity sectors, provides new insights and stresses the importance of tools to follow the overall performance of resource allocation. Managers of innovative organizations recognize the very powerful features of the Balanced Scorecard (BSC) in monitoring and linking strategic resources of both tangible and intangible natures. Thirdly, this research, with a view to enrich the field of intangible natures, points out some aspects for future research areas, bearing in mind the relevance of this research area confirmed by managers of the major innovative organizations. Thus, it provides prominent information for both academia and innovative organizations.

Resource Allocation Strategies in Cognitive Radio Networks Under QoS Constraints

2013 ◽  
pp. 81-104
Author(s):  
Stavroula Vassaki ◽  
Marios I. Poulakis ◽  
Athanasios D. Panagopoulos ◽  
Philip Constantinou
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Effective Capacity ◽  
Future Research ◽  
Capacity Theory ◽  
Wireless Users ◽  
Future Research Directions ◽  
Resource Allocation Schemes ◽  
Efficient Mechanisms

The rapid growth of spectral resources’ demands, as well as the increasing Quality of Service (QoS) requirements of wireless users have led to the necessity for new resource allocation schemes which will take into account the differentiated QoS needs of each wireless user. Towards this direction, the researchers have introduced the concept of effective capacity, which is defined as the maximum rate that the channel can support in order to guarantee a specified QoS requirement. This concept has been considered as a “bridge” among the physical layer characteristics and the upper-layer metrics of QoS. During the last years, it has been widely employed for resource allocation problems in various wireless networks leading to efficient mechanisms. This chapter focuses on the employment of the effective capacity theory in Cognitive Radio (CR) systems, presenting an extensive survey on QoS-driven resource allocation schemes proposed in the literature. Some useful conclusions are presented and future research directions on this subject are highlighted and discussed.

scholarly journals A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends and Challenges

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Guan Gui ◽  
Guoquan Li ◽  
Miao Liu ◽  
Haris Gacanin ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Networks ◽  
Spectrum Sharing ◽  
Limited Resource ◽  
Small Cells ◽  
Future Research ◽  
Sixth Generation ◽  
Communication Environments ◽  
Efficient Resource ◽  
Comprehensive Survey

In the fifth-generation (5G) wireless communications system, various service requirements under different communication environments are expected to be satisfied. As a new evolution network structure, heterogeneous networks (HetNet) have been fully studied in recent years. In contrast to conventional homogeneous networks, the key feature of HetNet is to increase the opportunity of spatial resource reuse and improve the quality of service of users by allowing small cells to cooperate in macrocell networks. However, since the mutual interference among different users and the limited resource are existing in HetNets, efficient resource allocation (RA) schemes are very important to reduce the interference and achieve spectrum sharing. In this paper, we provide a comprehensive survey on RA in HetNets for 5G communications. Specifically, we first introduce the definition and different network scenarios of HetNet. Second, RA models are discussed. Then, we present classification to analyze current RA schemes in the existing references. Finally, some challenging open issues and future research trends are addressed in this field. We also provide two effective approaches for the sixth-generation (6G) communications to solve the RA problems of future HetNets, namely, a learning-based approach and a control theory-based approach. This paper provides important information on HetNets, which can be used to guide the development of more efficient RA schemes in this area.

scholarly journals A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends and Challenges

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Guan Gui ◽  
Guoquan Li ◽  
Miao Liu ◽  
Haris Gacanin ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Networks ◽  
Spectrum Sharing ◽  
Limited Resource ◽  
Small Cells ◽  
Future Research ◽  
Sixth Generation ◽  
Communication Environments ◽  
Efficient Resource ◽  
Comprehensive Survey

In the fifth-generation (5G) wireless communications system, various service requirements under different communication environments are expected to be satisfied. As a new evolution network structure, heterogeneous networks (HetNet) have been fully studied in recent years. In contrast to conventional homogeneous networks, the key feature of HetNet is to increase the opportunity of spatial resource reuse and improve the quality of service of users by allowing small cells to cooperate in macrocell networks. However, since the mutual interference among different users and the limited resource are existing in HetNets, efficient resource allocation (RA) schemes are very important to reduce the interference and achieve spectrum sharing. In this paper, we provide a comprehensive survey on RA in HetNets for 5G communications. Specifically, we first introduce the definition and different network scenarios of HetNet. Second, RA models are discussed. Then, we present classification to analyze current RA schemes in the existing references. Finally, some challenging open issues and future research trends are addressed in this field. We also provide two effective approaches for the sixth-generation (6G) communications to solve the RA problems of future HetNets, namely, a learning-based approach and a control theory-based approach. This paper provides important information on HetNets, which can be used to guide the development of more efficient RA schemes in this area.

scholarly journals Revisiting of Channel Access Mechanisms in Mobile Wireless Networks through Exploiting Physical Layer Technologies

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Junmei Yao ◽  
Jun Xu ◽  
Yue Ling Che ◽  
Kaishun Wu ◽  
Wei Lou
Keyword(s):  
Network Performance ◽  
Rapid Development ◽  
Interference Management ◽  
Local Area ◽  
Physical Layer ◽  
Network Throughput ◽  
Future Research ◽  
Channel Access ◽  
Node Mobility ◽  
Hidden Terminal

The wireless local area networks (WLANs) have been widely deployed with the rapid development of mobile devices and have further been brought into new applications with infrastructure mobility due to the growth of unmanned aerial vehicles (UAVs). However, the WLANs still face persistent challenge on increasing the network throughput to meet the customer’s requirement and fight against the node mobility. Interference is a well-known issue that would degrade the network performance due to the broadcast characteristics of the wireless signals. Moreover, with infrastructure mobility, the interference becomes the key obstacle in pursuing the channel capacity. Legacy interference management mechanism through the channel access control in the MAC layer design of the 802.11 standard has some well-known drawbacks, such as exposed and hidden terminal problems, inefficient rate adaptation, and retransmission schemes, making the efficient interference management an everlasting research topic over the years. Recently, interference management through exploiting physical layer mechanisms has attracted much research interest and has been proven to be a promising way to improve the network throughput, especially under the infrastructure mobility scenarios which provides more indicators for node dynamics. In this paper, we introduce a series of representative physical layer techniques and analyze how they are exploited for interference management to improve the network performance. We also provide some discussions about the research challenges and give potential future research topics in this area.

scholarly journals Resource Allocation using Deep Learning in Mobile Small Cell Networks

2021 ◽  
Author(s):  
Saniya Zafar ◽  
sobia Jangsher ◽  
Arafat Al-Dweik
Keyword(s):  
Resource Allocation ◽  
Deep Learning ◽  
Network Performance ◽  
Short Term Memory ◽  
High Mobility ◽  
Small Cells ◽  
Time Interval ◽  
Performance Simulation ◽  
Interference Graph

The deployment of mobile-Small cells (mScs) is widely adopted to intensify the quality-of-service (QoS) in high mobility vehicles. However, the rapidly varying interference patterns among densely deployed mScs make the resource allocation (RA) highly challenging. In such scenarios, RA problem needs to be solved nearly in real-time, which can be considered as drawback for most existing RA algorithms. To overcome this constraint and solve the RA problem efficiently, we use deep learning (DL) in this work due to its ability to leverage the historical data in RA problem and to deal with computationally expensive tasks offline. More specifically, this paper considers the RA problem in vehicular environment comprising of city buses, where DL is explored for optimization of network performance. Simulation results reveal that RA in a network using Long Short-Term Memory (LSTM) algorithm outperforms other machine learning (ML) and DL-based RA mechanisms. Moreover, RA using LSTM provides less accurate results as compared to existing Time Interval Dependent Interference Graph (TIDIG)-based, and Threshold Percentage Dependent Interference Graph (TPDIG)-based RA but shows improved results when compared to RA using Global Positioning System Dependent Interference Graph (GPSDIG). However, the proposed scheme is computationally less expensive in comparison with TIDIG and TPDIG-based algorithms.

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