scholarly journals Propagation-Model-Free Base Station Deployment for Mobile Networks: Integrating Machine Learning and Heuristic Methods

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 83375-83386 ◽  
Author(s):  
Lingcheng Dai ◽  
Hongtao Zhang
Keyword(s):  
Machine Learning ◽  
Mobile Networks ◽  
Base Station ◽  
Propagation Model ◽  
Heuristic Methods ◽  
Free Base ◽  
Model Free

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

scholarly journals Study of 5G-NR-MIMO Links in the Presence of an Interferer

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 732
Author(s):  
Avner Elgam ◽  
Yael Balal ◽  
Yosef Pinhasi
Keyword(s):  
Mobile Networks ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Local Area ◽  
Maximum Energy ◽  
Base Station ◽  
Small Cells ◽  
Diversity Coding ◽  
Shift Keying ◽  
Input Multiple Output

Many communication systems are based on the Multiple Input, Multiple Output (MIMO) scheme, and Orthogonal Space–time Block Transmit diversity Coding (OSTBC), combined with Maximal Ratio Receive Combining (MRRC), to create an optimal diversity system. A system with optimal diversity fixes and optimizes the channel’s effects under multi-path and Rayleigh fading with maximum energy efficiency; however, the challenge does not end with dealing with the channel destruction of the multi-path impacts. Susceptibility to interference is a significant vulnerability in future wireless mobile networks. The 5th Generation New Radio (5G-NR) technologies bring hundreds of small cells and pieces of User Equipment (UE) per indoor or outdoor local area scenario under a specific Long Term Evolution (LTE)-based station (e-NodeB), or under 5G-NR base-station (g-NodeB). It is necessary to study issues that deal with many interference signals, and smart jammers from advanced communication equipment cause deterioration in the links between the UE, the small cells, and the NodeB. In this paper, we study and present the significant impact and performances of 2×2 Alamouti Phase-Shift Keying (PSK) modulation techniques in the presence of an interferer and a smart jammer. The destructive effects affecting the MIMO array and the advanced diversity technique without closed-loop MIMO are analyzed. The performance is evaluated in terms of Bit Error Rate (BER) vs. Signal to Interference Ratio (SIR). In addition, we proved the impairment of the orthogonal spectrum assumption mathematically.

scholarly journals Model-free machine learning of wireless SISO/MIMO communications

2021 ◽  
Author(s):  
Dolores García ◽  
Jesus O. Lacruz ◽  
Damiano Badini ◽  
Danilo De Donno ◽  
Joerg Widmer
Keyword(s):  
Machine Learning ◽  
Mimo Communications ◽  
Model Free ◽  
Free Machine

scholarly journals MEASUREMENTSBASEDEVALUATION OF PATHLOSSEXPONENTS IN URBAN OUTDOORENVIRONMENTS

2021 ◽  
Vol 9 (03) ◽  
pp. 72-79
Author(s):  
Akohoule Alex ◽  
◽  
Bamba Aliou ◽  
Kamagate Aladji ◽  
Konate Adama ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Average Power ◽  
Path Loss ◽  
Wireless Channel ◽  
Propagation Model ◽  
Strong Impact ◽  
Efficient Design ◽  
Path Loss Exponent ◽  
Outdoor Environments ◽  
The Impact

In wireless networks, propagation models are used to assess the received power signal and estimate the propagation channel. These models depend on the pathloss exponent (PLE) which is one of the main parameters to characterize the propagation environment. Indeed, in the wireless channel, the path loss exponent has a strong impact on the quality of the links and must therefore be estimated with precision for an efficient design and operation of the wireless network. This paper addresses the issue of path loss exponents estimation for mobile networks in four outdoor environments. This study is based on measurements carried out in four outdoor environments at the frequency of 2600 MHz within a bandwidth of 70 MHz. It evaluates the path loss exponent, and the impact of obstacles present in the environments. The parameters of the propagation model determined from the measurements show that the average power of the received signal decreases logarithmically with the distance. We obtained path loss exponents values of 4.8, 3.53, 3.6 and 3.99 for the site 1, site 2, site 3 and site 4, respectively. Clearly the density of the obstacles has an impact on the path loss exponents and our study shows that the received signal decrease faster as the transmitter and receiver separation in the dense environments.

scholarly journals The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Zhang ◽  
Bin Chen ◽  
Liang Ma ◽  
Zhen Li ◽  
Zhichao Song ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Ebola Virus ◽  
Virus Disease ◽  
Propagation Model ◽  
Propagation Mechanism ◽  
Chinese Government ◽  
Emergency Plans ◽  
Artificial Society ◽  
The City

Ebola virus disease (EVD) distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, in recent years, computational experiments based on artificial society appeared, providing a new approach to study the propagation of EVD and analyze the corresponding interventions. Therefore, the rationality of artificial society is the key to the accuracy and reliability of experiment results. Individuals’ behaviors along with travel mode directly affect the propagation among individuals. Firstly, artificial Beijing is reconstructed based on geodemographics and machine learning is involved to optimize individuals’ behaviors. Meanwhile, Ebola course model and propagation model are built, according to the parameters in West Africa. Subsequently, propagation mechanism of EVD is analyzed, epidemic scenario is predicted, and corresponding interventions are presented. Finally, by simulating the emergency responses of Chinese government, the conclusion is finally drawn that Ebola is impossible to outbreak in large scale in the city of Beijing.

Enabling continuous connectivity services for ambrosus blockchain application by incorporating 5G-multilevel machine learning orchestrations

2022 ◽  
pp. 1-16
Author(s):  
Nagaraj Varatharaj ◽  
Sumithira Thulasimani Ramalingam
Keyword(s):  
Machine Learning ◽  
Wireless Networks ◽  
High Speed ◽  
Dynamic Condition ◽  
Main Idea ◽  
Base Station ◽  
Performance Comparison ◽  
Wide Range ◽  
Unit Layer ◽  
Block Chain

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% .

Optimizing the Traffic of Voice Core Domain in UMTS Network through RNC Re-Homing

2012 ◽  
pp. 227-240
Author(s):  
Ye Ouyang ◽  
Hosein Fallah
Keyword(s):  
Mobile Networks ◽  
Base Station ◽  
Third Generation ◽  
Core Network ◽  
Core Domain ◽  
Network Controller ◽  
Next Generation Mobile Networks ◽  
The Impact ◽  
Umts Networks

The past few years have seen mobile operators transition to next-generation mobile networks, specifically from third-generation networks (3G) to long term evolution (LTE). This paper describes the basic architecture and topology of UMTS R4 core network and introduces two options in network planning, i.e., flat structure or layered structure. This paper introduces the re-homing of radio network controller (RNC) and base station controller (BSC) and studies the impact on the performance of voice core of UMTS networks. The proposed RNC re-homing models are created and analyzed for voice core of UMTS networks. The paper concludes that the appropriate RNC re-homing optimizes the traffic of voice core in UMTS network.

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