scholarly journals 5G Network Planning under Service and EMF Constraints: Formulation and Solutions

2021 ◽  
pp. 1-1
Author(s):  
Luca Chiaraviglio ◽  
Cristian Di Paolo ◽  
Nicola Blefari Melazzi
Keyword(s):  
Network Planning ◽  
5G Network

Estimation of Parameters of 5G Network Dimensioning

2021 ◽  
Vol 10 (2) ◽  
pp. 15-32
Author(s):  
Henok M. Besfat ◽  
Zelalem Hailu Gebeyehu ◽  
Sudhir K. Routray
Keyword(s):  
Network Planning ◽  
Network Capacity ◽  
Network Coverage ◽  
Estimation Of Parameters ◽  
Optical Components ◽  
Fifth Generation ◽  
Planning And Design ◽  
Network Dimensioning ◽  
Mathematical Expressions ◽  
5G Network

Cellular network traffic increases rapidly, and new services are introduced every year. For proper planning and design of such networks, exact requirements must be known with good accuracy. Dimensioning is an important part of network planning and design. Dimensioning is essential to determine the network requirements. In the coming years, fifth-generation (5G) will be deployed widely. 5G infrastructure is hybrid of wireless and optical components. For 5G network dimensioning, there is a need of a hybrid model. In this paper, the authors develop mathematical expressions for 5G network dimensioning. They use ITU proposed typical 5G network provisions to estimate bandwidth, network capacity, coverage, and capital expenditures. They also establish the correlation between the optical and the wireless parts. The expressions developed in this work can be used for the fast estimation of network coverage. So, this model can play important roles for 5G network planning and design.

scholarly journals A Data-Driven Multiobjective Optimization Framework for Hyperdense 5G Network Planning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 169423-169443
Author(s):  
Beneyam Berehanu Haile ◽  
Edward Mutafungwa ◽  
Jyri Hamalainen
Keyword(s):  
Multiobjective Optimization ◽  
Network Planning ◽  
Data Driven ◽  
Optimization Framework ◽  
5G Network

scholarly journals A Genetic Algorithm with Location Intelligence Method for Energy Optimization in 5G Wireless Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Ruchi Sachan ◽  
Tae Jong Choi ◽  
Chang Wook Ahn
Keyword(s):  
Genetic Algorithm ◽  
Network Planning ◽  
High Capacity ◽  
Optimal Configuration ◽  
Smart Devices ◽  
Data Traffic ◽  
De Algorithm ◽  
Decision Variables ◽  
Real Coded Genetic Algorithm ◽  
5G Network

The exponential growth in data traffic due to the modernization of smart devices has resulted in the need for a high-capacity wireless network in the future. To successfully deploy 5G network, it must be capable of handling the growth in the data traffic. The increasing amount of traffic volume puts excessive stress on the important factors of the resource allocation methods such as scalability and throughput. In this paper, we define a network planning as an optimization problem with the decision variables such as transmission power and transmitter (BS) location in 5G networks. The decision variables lent themselves to interesting implementation using several heuristic approaches, such as differential evolution (DE) algorithm and Real-coded Genetic Algorithm (RGA). The key contribution of this paper is that we modified RGA-based method to find the optimal configuration of BSs not only by just offering an optimal coverage of underutilized BSs but also by optimizing the amounts of power consumption. A comparison is also carried out to evaluate the performance of the conventional approach of DE and standard RGA with our modified RGA approach. The experimental results showed that our modified RGA can find the optimal configuration of 5G/LTE network planning problems, which is better performed than DE and standard RGA.

scholarly journals PLANNING OF 5G NETWORK PATH LOSS IN GEOMETRY BASED STOCHASTIC CONCEPT BY USING LINEAR REGRESSION METHODS

Kursor ◽  
2020 ◽  
Vol 10 (4) ◽  
Author(s):  
Achmad Ubaidillah ◽  
S. Ida Kholida
Keyword(s):  
Linear Regression ◽  
Linear Regression Analysis ◽  
Network Planning ◽  
Path Loss ◽  
Regression Method ◽  
Linear Regression Method ◽  
Regression Methods ◽  
5G Network ◽  
Forecasting System ◽  
Better Than

This research is a continuation of several previous studies that made 5G network planning using the Free Space Reference Path Loss model. In this study, a 5G network path loss planning was made using the Geometry Based Stochastic model. A forecasting system is created that connects the path loss with the distance between the transmitter and the receiver antenna using the linear regression method. It is important to look at 5G network planning on a different side. The result shows that the path loss value in the light of sight condition is better than the non-light of sight condition with the lowest value of 94.4271 dB at the frequency of 28 GHz and 99.5856 dB at the 73 GHz frequency. Linear Regression analysis shows that the best path loss calculation is the frequency 28 GHz of LOS conditions with MSE is 0.001 and the standard deviation error is 0.0319.

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