Experimental Evaluation of Information Dissemination Scheme Considering Mobile Network Base Station Load in Wireless Networks

Author(s):  
Tatsuki Horai ◽  
Tomoyuki Ohta ◽  
Yoshiaki Kakuda
Author(s):  
Shuja Ansari ◽  
Ahmad Taha ◽  
Kia Dashtipour ◽  
Yusuf Sambo ◽  
Qammer H. Abbasi ◽  
...  

The increasing popularity of Unmanned Aerial Vehicles (UAV) has resulted in exponential growth of the market owing to numerous applications that have been facilitated by advances in battery technology and wireless communications. Given the successes of UAVs thus far, researchers are already gearing towards aerial transport systems that consist of dense deployment of both UAVs and Personal Aerial Vehicles (PAVs) with human passengers. Although the fifth-generation mobile network (5G) key performance indicators have been optimised to support drone use cases for both high data rates and low latency applications, future aerial transport systems will require stricter network key performance indicators to support the expected massive deployment of aerial vehicles taking into account network capacity and distance between the base station and the aerial vehicles, among others. In this article, we present our perspective, vision, architecture, requirements and key performance indicators for future aerial wireless networks supported by 6G for Urban Air Mobility (UAM). Furthermore, we review key enabling technologies and discuss future challenges for incorporating aerial wireless networks in 6G.


Author(s):  
V. Lyandres

Introduction:Effective synthesis of а mobile communication network includes joint optimisation of two processes: placement of base stations and frequency assignment. In real environments, the well-known cellular concept fails due to some reasons, such as not homogeneous traffic and non-isotropic wave propagation in the service area.Purpose:Looking for the universal method of finding a network structure close to the optimal.Results:The proposed approach is based on the idea of adaptive vector quantization of the network service area. As a result, it is reduced to a 2D discrete map split into zones with approximately equal number of service requests. In each zone, the algorithm finds such coordinates of its base station that provide the shortest average distance to all subscribers. This method takes into account the shortage of the a priory information about the current traffic, ensures maximum coverage of the service area, and what is not less important, significantly simplifies the process of frequency assignment.


2018 ◽  
Vol 140 ◽  
pp. 51-61 ◽  
Author(s):  
George Koufoudakis ◽  
Konstantinos Oikonomou ◽  
Konstantinos Giannakis ◽  
Sonia Aïssa

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 32687-32699 ◽  
Author(s):  
Xiaoying Gan ◽  
Zhida Qin ◽  
Luoyi Fu ◽  
Xinbing Wang

2022 ◽  
pp. 1-16
Author(s):  
Nagaraj Varatharaj ◽  
Sumithira Thulasimani Ramalingam

Most revolutionary applications extending far beyond smartphones and high configured mobile device use to the future generation wireless networks’ are high potential capabilities in recent days. One of the advanced wireless networks and mobile technology is 5G, where it provides high speed, better reliability, and amended capacity. 5 G offers complete coverage, which is accommodates any IoT device, connectivity, and intelligent edge algorithms. So that 5 G has a high demand in a wide range of commercial applications. Ambrosus is a commercial company that integrates block-chain security, IoT network, and supply chain management for medical and food enterprises. This paper proposed a novel framework that integrates 5 G technology, Machine Learning (ML) algorithms, and block-chain security. The main idea of this work is to incorporate the 5 G technology into Machine learning architectures for the Ambrosus application. 5 G technology provides continuous connection among the network user/nodes, where choosing the right user, base station, and the controller is obtained by using for ML architecture. The proposed framework comprises 5 G technology incorporate, a novel network orchestration, Radio Access Network, and a centralized distributor, and a radio unit layer. The radio unit layer is used for integrating all the components of the framework. The ML algorithm is evaluated the dynamic condition of the base station, like as IoT nodes, Ambrosus users, channels, and the route to enhance the efficiency of the communication. The performance of the proposed framework is evaluated in terms of prediction by simulating the model in MATLAB software. From the performance comparison, it is noticed that the proposed unified architecture obtained 98.6% of accuracy which is higher than the accuracy of the existing decision tree algorithm 97.1% .


Author(s):  
Alberto Díez Albaladejo ◽  
Fabricio Gouveia ◽  
Marius Corici ◽  
Thomas Magedanz

Next Generation Mobile Networks (NGMNs) constitute the evolution of mobile network architectures towards a common IP based network. One of the main research topics in wireless networks architectures is QoS control and provisioning. Different approaches to this issue have been described. The introduction of the NGMNs is a major trend in telecommunications, but the heterogeneity of wireless accesses increases the challenges and complicates the design of QoS control and provisioning. This chapter provides an overview of the standard architectures for QoS control in Wireless networks (e.g. UMTS, WiFi, WiMAX, CDMA2000), as well as, the issues on this all-IP environment. It provides the state-of-the-art and the latest trends for converging networks to a common architecture. It also describes the challenges that appear in the design and deployment of QoS architectures for heterogeneous accesses and the available solutions. The Evolved Core from 3GPP is analyzed and described as a suitable and promising solution addressing these challenges.


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