Experimental Field Trials on MU-MIMO Transmissions for High SHF Wide-Band Massive MIMO in 5G

Sakai, Manabu; Kamohara, Kenichiro; Iura, Hiroki; Nishimoto, Hiroshi; Kazuaki, Ishioka; Murata, Yoshitaka; Yamamoto, Masayuki; Okazaki, Atsushi; Nonaka, Nobuhide; Suyama, Satoshi; Mashino, Jun; Okamura, Atsushi; Okumura, Yukihiko

doi:10.1109/twc.2019.2962766

Cited by 37 publications

(19 citation statements)

References 19 publications

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“…e functions are arranged in a form of a directed and acyclic graph. For instance, functions f (1) , f (2) , and f (3) , linked together form a chain:…”

Section: Dense Deep Neural Networkmentioning

confidence: 99%

“…Generally, these forms of chain structures are the most applied structures for neural networks. f (1) is known as the first layer, f (2) being the second layer of the network and other layers follow the same pattern. e depth of a model is defined by the entire length of the chain.…”

Section: Dense Deep Neural Networkmentioning

confidence: 99%

“…e unprecedented quest for rapid mobile traffic calls opens the way for emerging mobile communication systems [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…As pointed out in [2], a lot of research and development on 5G has been conducted before it is commercialized in the year 2020. e resurfacing of artificial intelligence with full force can bring an alternative methodology in solving 5G problems with likely better performance compared with the traditional methods [14]. e increased complexity of the cellular mobile network indicated that machine learning, a subset of artificial intelligence, has the potential to effectively improve the technologies of 5G wireless mobile networks [15].…”

Section: Introductionmentioning

confidence: 99%

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Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction

Almutairi

2022

Mathematical Problems in Engineering

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The advent of the 5G mobile network has brought a lot of benefits. However, it prompted new challenges on the 5G network cybersecurity defense system, resource management, energy, cache, and mobile network, therefore making the existing approaches obsolete to tackle the new challenges. As a result of that, research studies were conducted to investigate deep learning approaches in solving problems in 5G network and 5G powered Internet of Vehicles (IoVs). In this article, we present a survey on the applications of deep learning algorithms for solving problems in 5G mobile network and 5G powered IoV. The survey pointed out the recent advances on the adoption of deep learning variants in solving the challenges of 5G mobile network and 5G powered IoV. The deep learning algorithm solutions for security, energy, resource management, 5G-enabled IoV, and mobile network in 5G communication systems were presented including several other applications. New comprehensive taxonomies were created, and new comprehensive taxonomies were suggested, analysed, and presented. The challenges of the approaches are already discussed in the literature, and new perspective for solving the challenges was outlined and discussed. We believed that this article can stimulate new interest in practical applications of deep learning in 5G network and provide clear direction for novel approaches to expert researchers.

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“…e functions are arranged in a form of a directed and acyclic graph. For instance, functions f (1) , f (2) , and f (3) , linked together form a chain:…”

Section: Dense Deep Neural Networkmentioning

confidence: 99%

Section: Dense Deep Neural Networkmentioning

confidence: 99%

“…e unprecedented quest for rapid mobile traffic calls opens the way for emerging mobile communication systems [1,2].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction

Almutairi

2022

Mathematical Problems in Engineering

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“…Massive MIMO is expected to be one of the most promising technologies towards the fifth generation mobile communications (5G) and beyond. Implementation [2,3] and trials [4,5] are actively proceeded. Especially, massive array beamforming has a good match to millimeter wave communication [6] which suffers from link budget shortfall due to its high frequency.…”

Section: Introductionmentioning

confidence: 99%

Massive MIMO Systems: Present and Future

Maruta

Falcone

2020

Electronics

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Security in5Gand beyond recent advances and future challenges

Salahdine

Zhang

2022

Security and Privacy

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5G, 6G, and beyond (xG) technologies aim at delivering emerging services with new requirements and challenges, enabling full and hyper mobile connectivity over the world. These beyond 5G networks are expected to ensure better quality of service, very high data rate, improved network security, high capacity, low latency, and low cost. In order to meet these objectives, a number of key enabler technologies have been proposed including massive multiple input multiple output, small cells, mobile edge computing, software defined network, network function virtualization, heterogeneous networks, network slicing, cloud radio access network, ultra-dense network, energy efficiency, and spectrum sharing. Although, the potential interest of these technologies in the network, they opened the door to many security concerns and challenges making the network security one of the primary concerns of the future wireless communication networks. In this article, we investigated the recent advancements on the xG security issues resulted by each key enabler technologies. We analyzed how to secure the network while meeting the emerging promising services, users' demands, and service requirements. We also discussed how the security issues raised by these emerging technologies can be mitigated for efficient and secure communication.

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Experimental Field Trials on MU-MIMO Transmissions for High SHF Wide-Band Massive MIMO in 5G

Cited by 37 publications

References 19 publications

Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction

Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction

Massive MIMO Systems: Present and Future

Security in5Gand beyond recent advances and future challenges

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