scholarly journals Artificial intelligence techniques over the fifth generation mobile networks: a review

2021 ◽  
Vol 24 (1) ◽  
pp. 317
Author(s):  
Ashwaq N. Hassan ◽  
Sarab Al-Chlaihawi ◽  
Ahlam R. Khekan
Keyword(s):  
Artificial Intelligence ◽  
Mobile Networks ◽  
Human Error ◽  
Smart Cities ◽  
Mobile Network ◽  
Fourth Generation ◽  
Future Research ◽  
Artificial Intelligence Techniques ◽  
Fifth Generation ◽  
Sixth Generation

<span>A well Fifth generation (5G) mobile networks have been a common phrase in recent years. We have all heard this phrase and know its importance. By 2025, the number of devices based on the fifth generation of mobile networks will reach about 100 billion devices. By then, about 2.5 billion users are expected to consume more than a gigabyte of streamed data per month. 5G will play important roles in a variety of new areas, from smart homes and cars to smart cities, virtual reality and mobile augmented reality, and 4K video streaming. Bandwidth much higher than the fourth generation, more reliability and less latency are some of the features that distinguish this generation of mobile networks from previous generations.  Clearly, at first glance, these features may seem very impressive and useful to a mobile network, but these features will pose serious challenges for operators and communications companies. All of these features will lead to considerable complexity. Managing this network, preventing errors, and minimizing latency are some of the challenges that the 5th generation of mobile networks will bring. Therefore, the use of artificial intelligence and machine learning is a good way to solve these challenges. in other say, in such a situation, proper management of the 5G network must be done using powerful tools such as artificial intelligence. Various researches in this field are currently being carried out. Research that enables automated management and servicing and reduces human error as much as possible. In this paper, we will review the artificial intelligence techniques used in communications networks. Creating a robust and efficient communications network using artificial intelligence techniques is a great incentive for future research.</span><span> The importance of this issue is such that the sixth generation (6G) of cellular communications; There is a lot of emphasis on the use of artificial intelligence.</span>

scholarly journals Handover Parameters Optimisation Techniques in 5G Networks

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5202
Author(s):  
Wasan Kadhim Saad ◽  
Ibraheem Shayea ◽  
Bashar J. Hamza ◽  
Hafizal Mohamad ◽  
Yousef Ibrahim Daradkeh ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Mobile Network ◽  
Small Cells ◽  
Fourth Generation ◽  
Acceptable Solution ◽  
Massive Growth ◽  
Fifth Generation ◽  
5G Network ◽  
Simulation Results ◽  
The Impact

The massive growth of mobile users will spread to significant numbers of small cells for the Fifth Generation (5G) mobile network, which will overlap the fourth generation (4G) network. A tremendous increase in handover (HO) scenarios and HO rates will occur. Ensuring stable and reliable connection through the mobility of user equipment (UE) will become a major problem in future mobile networks. This problem will be magnified with the use of suboptimal handover control parameter (HCP) settings, which can be configured manually or automatically. Therefore, the aim of this study is to investigate the impact of different HCP settings on the performance of 5G network. Several system scenarios are proposed and investigated based on different HCP settings and mobile speed scenarios. The different mobile speeds are expected to demonstrate the influence of many proposed system scenarios on 5G network execution. We conducted simulations utilizing MATLAB software and its related tools. Evaluation comparisons were performed in terms of handover probability (HOP), ping-pong handover probability (PPHP) and outage probability (OP). The 5G network framework has been employed to evaluate the proposed system scenarios used. The simulation results reveal that there is a trade-off in the results obtained from various systems. The use of lower HCP settings provides noticeable enhancements compared to higher HCP settings in terms of OP. Simultaneously, the use of lower HCP settings provides noticeable drawbacks compared to higher HCP settings in terms of high PPHP for all scenarios of mobile speed. The simulation results show that medium HCP settings may be the acceptable solution if one of these systems is applied. This study emphasises the application of automatic self-optimisation (ASO) functions as the best solution that considers user experience.

scholarly journals Data Traffic Based on Slicing in a 5G Smart Uplink System

Telecom IT ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 44-54
Author(s):  
A. Grebenshchikova ◽  
Elagin V.
Keyword(s):  
Mobile Networks ◽  
Data Transfer ◽  
Relay Node ◽  
Mobile Network ◽  
Video Stream ◽  
Base Station ◽  
Smart Devices ◽  
Future Research ◽  
Data Traffic ◽  
Fifth Generation

The paper considers the data traffic based on slicing in a 5g mobile network uplink system. Slicing is a promising technology for the fifth generation of networks that provides optimal quality of QOS services for each specific user or group of users. Data traffic that is processed by cellular networks increases every year. Therefore, we should consider all set of traffic from VoIP to M2M devices. For example, smart devices in the healthcare system transmit big data that is sensitive to latency, but also a video stream that requires minimal latency in certain cases. The paper focuses on the successful processing of traffic through a relay node, donor microstates, and a base station. All traffic is divided into three levels of QoS segmentation: sensitive, less sensitive, and low-sensitivity, using the AnyLogic simulation program. For fifth-generation 5G networks, achieving minimum latency and maximum data transfer speed within QoS is an important implementation condition. Therefore, in this paper, using simulation modeling, the main and possible results of each segment in the new generation of mobile networks are obtained. The use of a relay node in conjunction with micro-stations can ensure optimal station load and successful data processing. Also, the solutions outlined in this paper will allow you to identify a number of areas for future research to assess possible ways to design new mobile networks, or improve existing ones.

scholarly journals Image-Based Automatic Watermeter Reading under Challenging Environments

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 434
Author(s):  
Qingqi Hong ◽  
Yiwei Ding ◽  
Jinpeng Lin ◽  
Meihong Wang ◽  
Qingyang Wei ◽  
...  
Keyword(s):  
Smart Cities ◽  
Rapid Development ◽  
Mobile Network ◽  
Spatial Layout ◽  
Single Image ◽  
Automatic Instrument ◽  
Intelligent Sensors ◽  
Fifth Generation ◽  
Instrument Reading ◽  
Network Technologies

With the rapid development of artificial intelligence and fifth-generation mobile network technologies, automatic instrument reading has become an increasingly important topic for intelligent sensors in smart cities. We propose a full pipeline to automatically read watermeters based on a single image, using deep learning methods to provide new technical support for an intelligent water meter reading. To handle the various challenging environments where watermeters reside, our pipeline disentangled the task into individual subtasks based on the structures of typical watermeters. These subtasks include component localization, orientation alignment, spatial layout guidance reading, and regression-based pointer reading. The devised algorithms for orientation alignment and spatial layout guidance are tailored to improve the robustness of our neural network. We also collect images of watermeters in real scenes and build a dataset for training and evaluation. Experimental results demonstrate the effectiveness of the proposed method even under challenging environments with varying lighting, occlusions, and different orientations. Thanks to the lightweight algorithms adopted in our pipeline, the system can be easily deployed and fully automated.

scholarly journals Network Amelioration, AI Automation and Future Integration in Wireless Networks

2021 ◽  
Vol 9 (8) ◽  
pp. 2607-2613
Author(s):  
Marzook Khatri
Keyword(s):  
Artificial Intelligence ◽  
Communication Networks ◽  
Mobile Networks ◽  
Network Virtualization ◽  
Mobile Network ◽  
Data Access ◽  
Detailed Comparison ◽  
Mobile Industry ◽  
Generation Network ◽  
Network Operations

Abstract: The deployment of 5G mobile communication networks is just getting started right now. There are numerous technologies available today, each capable of fulfilling activities such as enabling voice traffic via voice over IP (VoIP), providing broadband data access in mobile environments, and so on. However, there is a pressing need to implement technology that can bring all of these systems together into a single unified system. Because it is all about smoothly integrating terminals, networks, and applications, 8G presents a solution to this dilemma. In this work, an attempt is made to provide a study of various cellular technologies, such as 4G, 5G, 6G, 7G, and FG, as well as a detailed comparison between them. With the introduction of network virtualization and the implementation of 5G/IoT, mobile networks will become more complicated and offer more diverse services. This raises concerns about a considerable increase in the workload of network operations. Meanwhile, artificial intelligence (AI) is advancing rapidly and is projected to alleviate human resource shortages in a variety of industries. Similarly, the mobile industry is gaining traction in the application of artificial intelligence (AI) to network operations in order to improve the efficiency of mobile network operations. This paper will address the idea of using AI technology to network operations and will give various use examples to demonstrate that AI-driven network operations have a bright future. Keywords: 5G & 6G networks, Artificial Intelligence, Next generation network, Future Advancement.

scholarly journals Study and Investigation on 5G Technology: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 26
Author(s):  
Ramraj Dangi ◽  
Praveen Lalwani ◽  
Gaurav Choudhary ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Mobile Networks ◽  
High Speed ◽  
Future Research ◽  
Mobile System ◽  
Fifth Generation ◽  
Research Article ◽  
Next Generation Mobile Networks ◽  
Multiple Input ◽  
Multiple Challenges ◽  
Mobile Communication Technology

In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobile networks, 5G provides a high-speed internet facility, anytime, anywhere, for everyone. 5G is slightly different due to its novel features such as interconnecting people, controlling devices, objects, and machines. 5G mobile system will bring diverse levels of performance and capability, which will serve as new user experiences and connect new enterprises. Therefore, it is essential to know where the enterprise can utilize the benefits of 5G. In this research article, it was observed that extensive research and analysis unfolds different aspects, namely, millimeter wave (mmWave), massive multiple-input and multiple-output (Massive-MIMO), small cell, mobile edge computing (MEC), beamforming, different antenna technology, etc. This article’s main aim is to highlight some of the most recent enhancements made towards the 5G mobile system and discuss its future research objectives.

When Wearable Computing Meets Smart Cities

2019 ◽  
pp. 1356-1376 ◽  
Author(s):  
João Soares de Oliveira Neto ◽  
André Luis Meneses Silva ◽  
Fábio Nakano ◽  
José J. Pérez-Álcazar ◽  
Sergio T. Kofuji
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Urban Space ◽  
Universal Design ◽  
Smart Cities ◽  
Wearable Computing ◽  
Future Research ◽  
Successful Implementation ◽  
Persons With Disabilities

In this chapter, wearables are presented as assistive technology to support persons with disabilities (PwD) to face the urban space in an autonomous and independently way. In the Inclusive Smart City (ISC), everyone has to be able to access visual and audible information that so far are available just for people that can perfectly see and listen. Several concepts and technologies – such as Accessibility and Universal Design, Pervasive Computing, Wearable Computing, Internet of Things, Artificial Intelligence, and Cloud Computing – are associated to achieve this aim. Also, this chapter discusses some examples of use of wearables in the context of Smart Cities, states the importance of these devices to the successful implementation of Inclusive Smart Cities, as well as presenting challenges and future research opportunities in the field of wearables in ISC.

scholarly journals Sixth Generation (6G) Wireless Networks: Vision, Research Activities, Challenges and Potential Solutions

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 676 ◽  
Author(s):  
Mohammed H. Alsharif ◽  
Anabi Hilary Kelechi ◽  
Mahmoud A. Albreem ◽  
Shehzad Ashraf Chaudhry ◽  
M. Sultan Zia ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Communication Systems ◽  
Future Research ◽  
Competitive Edge ◽  
Fifth Generation ◽  
Research Activities ◽  
Sixth Generation ◽  
Critical Issues ◽  
Future Research Directions ◽  
Communication Needs

The standardization activities of the fifth generation communications are clearly over and deployment has commenced globally. To sustain the competitive edge of wireless networks, industrial and academia synergy have begun to conceptualize the next generation of wireless communication systems (namely, sixth generation, (6G)) aimed at laying the foundation for the stratification of the communication needs of the 2030s. In support of this vision, this study highlights the most promising lines of research from the recent literature in common directions for the 6G project. Its core contribution involves exploring the critical issues and key potential features of 6G communications, including: (i) vision and key features; (ii) challenges and potential solutions; and (iii) research activities. These controversial research topics were profoundly examined in relation to the motivation of their various sub-domains to achieve a precise, concrete, and concise conclusion. Thus, this article will contribute significantly to opening new horizons for future research directions.

scholarly journals Open-Source Based Testbed for Multioperator 4G/5G Infrastructure Sharing in Virtual Environments

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Ricardo Marco Alaez ◽  
Jose M. Alcaraz Calero ◽  
Qi Wang ◽  
Fatna Belqasmi ◽  
May El Barachi ◽  
...  
Keyword(s):  
Open Source ◽  
Mobile Networks ◽  
Fourth Generation ◽  
Mobile Telecommunication ◽  
Significant Saving ◽  
Design And Implementation ◽  
Fifth Generation ◽  
The Impact ◽  
Telecommunication Operators

Fourth-Generation (4G) mobile networks are based on Long-Term Evolution (LTE) technologies and are being deployed worldwide, while research on further evolution towards the Fifth Generation (5G) has been recently initiated. 5G will be featured with advanced network infrastructure sharing capabilities among different operators. Therefore, an open-source implementation of 4G/5G networks with this capability is crucial to enable early research in this area. The main contribution of this paper is the design and implementation of such a 4G/5G open-source testbed to investigate multioperator infrastructure sharing capabilities executed in virtual architectures. The proposed design and implementation enable the virtualization and sharing of some of the components of the LTE architecture. A testbed has been implemented and validated with intensive empirical experiments conducted to validate the suitability of virtualizing LTE components in virtual infrastructures (i.e., infrastructures with multitenancy sharing capabilities). The impact of the proposed technologies can lead to significant saving of both capital and operational costs for mobile telecommunication operators.

scholarly journals Artificial Intelligence and Machine Learning in 5G and beyond: A Survey and Perspectives

2021 ◽  
Author(s):  
Abdelfatteh Haidine ◽  
Fatima Zahra Salmam ◽  
Abdelhak Aqqal ◽  
Aziz Dahbi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Mobile Networks ◽  
Network Architecture ◽  
Mobile Network ◽  
Cost Effective ◽  
Mobile Internet ◽  
Network Function ◽  
New Radio ◽  
4G Lte

The deployment of 4G/LTE (Long Term Evolution) mobile network has solved the major challenge of high capacities, to build real broadband mobile Internet. This was possible mainly through very strong physical layer and flexible network architecture. However, the bandwidth hungry services have been developed in unprecedented way, such as virtual reality (VR), augmented reality (AR), etc. Furthermore, mobile networks are facing other new services with extremely demand of higher reliability and almost zero-latency performance, like vehicle communications or Internet-of-Vehicles (IoV). Using new radio interface based on massive MIMO, 5G has overcame some of these challenges. In addition, the adoption of software defend networks (SDN) and network function virtualization (NFV) has added a higher degree of flexibility allowing the operators to support very demanding services from different vertical markets. However, network operators are forced to consider a higher level of intelligence in their networks, in order to deeply and accurately learn the operating environment and users behaviors and needs. It is also important to forecast their evolution to build a pro-actively and efficiently (self-) updatable network. In this chapter, we describe the role of artificial intelligence and machine learning in 5G and beyond, to build cost-effective and adaptable performing next generation mobile network. Some practical use cases of AI/ML in network life cycle are discussed.

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