5G Architecture: Deployment scenarios and options

Rhayour, Amine El; Mazri, Tomader

doi:10.1109/isaect47714.2019.9069723

Cited by 24 publications

(9 citation statements)

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“…we will be able to deliver a 5G-like internet surfing to our subscribers' devices. 6 With EN-DC, we can theoretically have four different kinds of layouts. As shown in Figure 1.…”

Section: Architecture Of 5gmentioning

confidence: 99%

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A novel hybrid deep learning approach for 5G network traffic control and forecasting

Dangi

Lalwani

2022

Concurrency and Computation

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5G is planned to link not just traditional devices such as tablets and smartphones, but also smart devices, smart homes, autonomous vehicles, and industry 4.0 which significantly increases the amount of traffic over the network. Network function virtualization and software defined networks will be used heavily to create scalably and on-demand 5G architecture using virtual network functions. In this article, we proposed a unique approach to scaling 5G core network resources by predicting traffic load fluctuations using a hybrid model. Most researchers have presented deep learning models to anticipate regular traffic to improve services, however, these recommended models have failed to estimate traffic load during festivals to unexpected changes in traffic conditions. To solve this issue, we introduced CNN+LSTM, a hybrid model that combines CNN, and LSTM to forecast cumulative network traffic across particular intervals to scale up and properly estimate the availability of 5G network resources by leveraging traffic load variations. The suggested model surpasses the other tested deep learning models and existing techniques that forecast the output in both normal and abnormal traffic conditions, according to a comparison of the produced output with existing techniques.

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“…we will be able to deliver a 5G-like internet surfing to our subscribers' devices. 6 With EN-DC, we can theoretically have four different kinds of layouts. As shown in Figure 1.…”

Section: Architecture Of 5gmentioning

confidence: 99%

“…The disadvantage of this method is that it only addresses the 5G mobile broadband. However, by deploying this 5G secondary node, we will be able to deliver a 5G‐like internet surfing to our subscribers' devices 6 …”

Section: Introductionmentioning

confidence: 99%

A novel hybrid deep learning approach for 5G network traffic control and forecasting

Dangi

Lalwani

2022

Concurrency and Computation

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“…Currently, option 2 (stand alone-SA) and option 3 (non-standalone-NSA) are standardized, in which the 5G architecture provides 5G services using LTE architecture [206]. Following the guidelines in [207], Figure 3 shows 5G deployment options with frequency division and the supported existing architecture. Signaling techniques are capable of transmitting lower to higher data rates while considering several issues; i.e., slow beam-forming, lethargic synchronization consisting of large gaps in time slots, and pitiable channel efficiency as compared to existing techniques and conventional OFDM [208].…”

Section: Signaling Techniques For 5gmentioning

confidence: 99%

Machine Learning for Physical Layer in 5G and beyond Wireless Networks: A Survey

et al. 2021

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Fifth-generation (5G) technology will play a vital role in future wireless networks. The breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where billions of connected devices, people, and processes will be simultaneously served. The services provided by 5G include several use cases enabled by the enhanced mobile broadband, massive machine-type communications, and ultra-reliable low-latency communication. Fifth-generation networks potentially merge multiple networks on a single platform, providing a landscape for seamless connectivity, particularly for high-mobility devices. With their enhanced speed, 5G networks are prone to various research challenges. In this context, we provide a comprehensive survey on 5G technologies that emphasize machine learning-based solutions to cope with existing and future challenges. First, we discuss 5G network architecture and outline the key performance indicators compared to the previous and upcoming network generations. Second, we discuss next-generation wireless networks and their characteristics, applications, and use cases for fast connectivity to billions of devices. Then, we confer physical layer services, functions, and issues that decrease the signal quality. We also present studies on 5G network technologies, 5G propelling trends, and architectures that help to achieve the goals of 5G. Moreover, we discuss signaling techniques for 5G massive multiple-input and multiple-output and beam-forming techniques to enhance data rates with efficient spectrum sharing. Further, we review security and privacy concerns in 5G and standard bodies’ actionable recommendations for policy makers. Finally, we also discuss emerging challenges and future directions.

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“…5G emerges as the foundation for Enhanced Mobile Broadband (eMBB), Massive Machine-Type Communication (mMTC) and Ultra Reliable Low Latency Communication (URLLC) scenarios [3]. The initial implementation of the fifth generation network has been established initially following the NSA (Non-Standalone) architecture, which makes use of the LTE network as an interface for connecting 5G devices, adding greater throughput potential to the network [4]. This solution aims to save time and reduce costs for operators, since the entire LTE architecture already deployed serves as the core for the New Radio system.…”

Section: Introductionmentioning

confidence: 99%

Measurement Study on 5G NSA Architecture over Fading Channel

Silva¹,

Batalha²

2022

Signal &Amp; Image Processing Trends

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The 5G NR network with the Non-Standalone (NSA) architecture aims to advance with regard to throughput. When compared to fourth-generation mobile communication (4G LTE), the 5G has a higher data exchange capability through the gNB and the UE (User Equipment). For evaluation and optimization, it is necessary to carry out practical studies on the behaviour of the system in different environmental conditions, subject to attenuation processes, such as large-scale fading (Shading) and small-scale fading (Multipath propagation). This work has analysed the effect of the MCS (Modulation and Coding Scheme) variation on Throughput/BLER for, initially, a channel degraded by default AWGN, then the analysis extends to the multipath fading effect, which emulates more realistically a mobile communication network. The analysis confirmed the need for robust decision process algorithms in terms of MCS switching to maintain adequate data rates according to the requirement of each scenario with specific QoS (Quality of service), considering both 64 QAM and 256 QAM. The throughput degradation effect was more evident in higher-order modulations due to the higher probability of error inherent in the symbol arrangement. This study can be a key for understanding and developing huge modulation and coding schemes for fifth generation communications.

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5G Architecture: Deployment scenarios and options

Cited by 24 publications

References 0 publications

A novel hybrid deep learning approach for 5G network traffic control and forecasting

A novel hybrid deep learning approach for 5G network traffic control and forecasting

Machine Learning for Physical Layer in 5G and beyond Wireless Networks: A Survey

Measurement Study on 5G NSA Architecture over Fading Channel

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