Mobile Communication
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2022 ◽  
Vol 63 ◽  
pp. 102440
Author(s):  
Santha Vaithilingam ◽  
Mahendhiran Nair ◽  
Mary Macharia ◽  
Viswanath Venkatesh

Author(s):  
Arun Agarwal ◽  
Chandan Mohanta ◽  
Gourav Misra

The 5G mobile communication has now become commercially available. Furthermore, research across the globe has begun to improve the system beyond 5G and it is anticipated that 6G will deliver higher quality services and energy efficiency than 5G. The mobile network architecture needs to be redesigned to meet the requirements of the future. In the wake of the commercial rollout of the 5G model, both users and developers have realized the limitations of the system when compared to the system's original premise of being able to support the vast applications of connected devices. The article discusses the related technologies that can contribute to a robust and seamless network service. An upheaval in the use of vast mobile applications, especially those powered and managed by AI, has opened the doors to discussion on how mobile communication will evolve in the future. 6G is expected to go beyond being merely a mobile internet service provider to support the omnipresent AI services that will form the rock bed of end-to-end connected network-based devices. Moreover, the technologies that support 6G services and comprehensive research that enables this level of technical prowess have also been identified here. This paper presents a collective wide-angle vision that will facilitate a better understanding of the features of the 6G system.


2022 ◽  
Vol 1212 (1) ◽  
pp. 012046
Author(s):  
Yingchi Mao ◽  
Andri Pranolo ◽  
Leonel Hernandez ◽  
Aji Prasetya Wibawa ◽  
Zalik Nuryana

Abstract In this paper, we elaborate on artificial intelligence (AI) techniques used to improve the performance of mobile communication. This article describes brief AI approaches in mobile communication, several classics AI techniques, and the current AI approaches in wireless communication. The techniques contain fuzzy logic, neural networks, reinforcement learning, and AI techniques implemented on mobile communication. Some keys or terms challenges between AI and future mobile communication, not only 5G generation issues but also how the sixth generation (6G) of mobile networks will be driven to give stable networks and service types on huge mobile devices and data.


Author(s):  
S. K. Deepa ◽  
K. Viswabharathi ◽  
M. Priyadharshini ◽  
N. Mithra

5G is the status of technology, which has the ability to create new interfaces for the daily used devices and networking components. 5G plays a major role in connecting larger number of users to provide smarter and faster communications. The design of this model is mainly designed to achieve performance with reduced bandwidth and better coverage, reliability, and latency. Mainly, the perception behind the wireless technology and 5G is to reduce the load and to steady the technical solutions to facilitate applications for better mobile communication and utilized with latest applications in the business environment. Therefore , IoT (Internet of Things) & 5G plays a vital role in mobile applications & network for eg.,smart watches, health applications, smart cards, smart cities.MMW( Millimeter wave) frequency spectrum is used to achieve transmission of large amount of data.


2021 ◽  
Author(s):  
Jiafei Fu ◽  
Pengcheng Zhu ◽  
Jingyu Hua ◽  
Jiamin Li ◽  
Jiangang Wen

Abstract Smart Internet of Vehicles (IoV) as a promising application in Internet of Things (IoT) emerges with the development of the fifth generation mobile communication (5G). Nevertheless, the heterogeneous requirements of sufficient battery capacity, powerful computing ability and energy efficiency for electric vehicles face great challenges due to the explosive data growth in 5G and the sixth generation of mobile communication (6G) networks. In order to alleviate the deficiencies mentioned above, this paper proposes a mobile edge computing (MEC) enabled IoV system, in which electric vehicle nodes (eVNs) upload and download data through an anchor node (AN) which is integrated with a MEC server. Meanwhile, the anchor node transmitters radio signal to electric vehicles with simultaneous wireless information and power transfer (SWIPT) technology so as to compensate the battery limitation of eletric vehicles. Moreover, the anchor node equips with full-duplex (FD) and multi-input and multi-output (MIMO) technologies for futher improve the spectrum efficiency. Taking into account the issues above, we maximize the average energy efficiency of electric vehicles by jointly optimize the CPU frequency, vehicle transmitting power, computing tasks and uplink rate. In order to solve this nonconvex problem, we propose a novel alternate interior-point iterative scheme (AIIS) under the constraints of computing tasks, energy consumption and time latency. Numerical simulations demonstrate the effectiveness of the proposed scheme comparing with the benchmark schemes.


2022 ◽  
Vol 71 (2) ◽  
pp. 3243-3255
Author(s):  
Mohammed H. Alsharif ◽  
Raju Kannadasan ◽  
Amir Y. Hassan ◽  
Wael Z. Tawfik ◽  
Mun-Kyeom Kim ◽  
...  

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