scholarly journals On a Strategy of Mobile Networks Synthesis

2021 ◽  
Vol 20 ◽  
pp. 108-111
Author(s):  
Vladimir Lyandres
Keyword(s):  
Mobile Networks ◽  
Channel Assignment ◽  
Euclidean Distance ◽  
Base Station ◽  
Base Stations ◽  
Optimal Placement ◽  
Universal Method ◽  
Optimal Network ◽  
Adaptive Vector Quantization ◽  
Effective Design

Effective design of mobile communication network includes optimization of two bounded together processes: the network base stations placement and the channel assignment. In real environments the well-known cellular concept fails due to not uniformly spaced traffic and not isotropic wave propagation. We find a rather universal method for synthesis of a close to optimal network structure. The proposed design approach is based on the idea of adaptive vector quantization for a map with random traffic. As a result, the service zone of the network becomes discrete and is being transformed to a map with not equal cells and approximately equal number of requests in every one. This fact allows to apply the simplest periodic reuse pattern. The algorithm finds a point with minimal average Euclidean distance from all its requests. This point defines optimal placement of the corresponding base station. The approach guarantees maximum coverage

Mobile network synthesis strategy

2019 ◽  
pp. 98-101
Author(s):  
V. Lyandres
Keyword(s):  
Average Distance ◽  
Mobile Network ◽  
Base Station ◽  
Service Area ◽  
Base Stations ◽  
Frequency Assignment ◽  
Network Synthesis ◽  
Universal Method ◽  
Synthesis Strategy ◽  
Adaptive Vector Quantization

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.

Channel Assignment Strategies for Mobile Networks Using Fuzzy Petri Nets

2011 ◽  
Vol 467-469 ◽  
pp. 1662-1667
Author(s):  
Yi Shun Weng ◽  
Yi Sheng Huang
Keyword(s):  
Petri Nets ◽  
Mobile Networks ◽  
Channel Assignment ◽  
Power Level ◽  
Base Station ◽  
Base Stations ◽  
Mobile Cellular ◽  
Mobile Cellular Networks ◽  
Fuzzy Petri Nets ◽  
Selection Of

In mobile cellular networks, the mobile devices need to handoff to different base stations based on certain criteria. And also fuzzy Petri nets can support an effective rule to deduce the inexact information. Based on the reasons, this paper focuses on the use of fuzzy Petri nets to model the handoff region for obtaining optimal channel assignment schemes. In this paper, a fuzzy logic based scheme for selection of base station is presented. The scheme considers two cover regions, namely, dual-BSs fuzzy assignment handoff and triple-BSs fuzzy assignment handoff of each base station to arrive at a fuzzy handoff decision regarding handoff to any particular base station. For comparison, the conventional power level based handoff scheme is also considered.

scholarly journals Handover Management for D2D Communication in 5G Networks

2020 ◽  
Vol 10 (12) ◽  
pp. 4409
Author(s):  
Wei Kuang Lai ◽  
Chin-Shiuh Shieh ◽  
Fu-Sheng Chou ◽  
Chia-Yu Hsu ◽  
Meng-Han Shen
Keyword(s):  
Mobile Networks ◽  
Base Station ◽  
Base Stations ◽  
D2d Communication ◽  
Expected Improvement ◽  
5G Networks ◽  
Handover Management ◽  
Current Standard ◽  
Handover Procedure ◽  
Device To Device

This study addresses the handover management issue for Device-to-Device communication in fifth-generation (5G) networks. The Third Generation Partnership Project (3GPP) drafted a standard for proximity services (ProSe), also named device-to-device (D2D) communication, which is a promising technology in offering higher throughput and lower latency services to end users. Handover is an essential issue in wireless mobile networks due to the mobility of user equipment (UE). Specifically, we need to transfer an ongoing connection from an old E-UTRAN Node B (eNB) to a new one, so that the UE can retain its connectivity. In the data plane, both parties of a D2D pair can communicate directly with each other without the involvement of the base station. However, in the control plane, devices must be connected to the eNB for tasks such as power control and resource allocation. In the current standard of handover scheme, the number of unnecessary handovers would be increased by the effect of shadowing fading on two devices. More important, the handover mechanism for D2D pairs is not standardized yet. LTE-A only considers the handover procedure of a single user. Therefore, when a D2D pair moves across cell boundaries, the control channels of the two UEs may connect to different base stations and result in increased latency due to the exchange of D2D related control messages. Hence, we propose a handover management scheme for D2D communication to let both parties of a D2D pair handover to the same destination eNB at the same time. By doing so, the number of unnecessary handovers, as well as the handover latency, can be reduced. In the proposed method, we predict the destination eNB of D2D users based on their movements and the received signal characteristics. Subsequently, we make a handover decision for each D2D pair by jointly factoring in the signal quality and connection stability. Expected improvement can be attained, as revealed in the simulation. Unnecessary handover can be avoided. Consequently, both UEs of a D2D pair reside in the same cell and, therefore, result in increased throughput and decreased delay.

scholarly journals Performance measurement of small-cells deployed under a heterogeneous network: an analysis of the co-existence of small-cells with the macro‑cell in 5G NR

2021 ◽  
Author(s):  
Mobasshir Mahbub ◽  
Bobby Barua
Keyword(s):  
Mobile Networks ◽  
Heterogeneous Network ◽  
Power Efficiency ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
Small Cells ◽  
Macro Cell ◽  
Received Power ◽  
Implementation Costs

Abstract Advancements of cellular networks such as 4G and 5G proposed the collaboration of small-cell technologies in mobile networks and constructed a heterogeneous network (HetNet) for collaborative connectivity. There are many benefits of small-cell-based collective communication such as the increase of device capability in indoor/outdoor locations, enhancement of wireless coverage, improved signal efficiency, lower implementation costs of gNB (Next-generation Base Station introduced in 5G), etc. The integration of small-cells by deploying low-power BSs (base stations) in conventional macro-gNBs was investigated as a convenient and economical way of raising the potentials of a cellular network with high demand from consumers. The fusion of small-cells with macro-cells offers increased coverage and capacity for heterogeneous networks. Therefore, the research aimed to realize the performance of a small-cell deployed under a macro-cell in a two-tier heterogeneous network. The research first modified the reference equation for measuring the received power by introducing the transmitter and receiver gain. The paper then measured the SINR, throughput, spectral efficiency, and power efficiency for both downlink and uplink by empirical simulation. The research further enlisted the notable outcomes after examining the simulation results and discussed some relevant research scopes in the concluding sections of the paper.

scholarly journals Passive Method for Estimating Available Throughput for Autonomous Off-Peak Data Transfer

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Kozo Satoda ◽  
Eiji Takahashi ◽  
Takeo Onishi ◽  
Takayuki Suzuki ◽  
Daisuke Ohta ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Data Transfer ◽  
Peak Load ◽  
Base Station ◽  
Base Stations ◽  
Recent Analysis ◽  
Data Traffic ◽  
End User ◽  
Lte Networks

Large demands for mobile traffic subject base stations to frequent short-term and sharp peak loads. Recent analysis of data traffic on commercial mobile networks reported that the traffic peaks can be reduced by an average of 40% without compromising the quality of experience provided to the end user, if a peak load can be shifted for at most 20 s. To reduce peak traffic, we previously proposed a method for off-peak data transfer, with which user equipment (UE) autonomously delays receiving data, and a peak load on a base station can be shifted. In terms of off-peak transfer of data, a significant problem is determining how each UE estimates available throughput. In this paper we propose a method of passively estimating available throughput of each UE. We evaluated the effectiveness of the proposed method through experiments on experimental and commercial LTE networks. The results indicate that our method obtains more than a 0.7 correlation between actual available throughput and estimated throughput.

scholarly journals Base Station Energy Efficiency Improvement for Next Generation Mobile Networks

2017 ◽  
Vol 63 (2) ◽  
pp. 187-194 ◽  
Author(s):  
Weston Mwashita ◽  
Marcel Ohanga Odhiambo
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Carbon Dioxide Emissions ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Data Traffic ◽  
Energy Efficiency Improvement ◽  
Next Generation Mobile Networks ◽  
Operational Expenditure

Abstract As more and more Base Stations (BSs) are being deployed by mobile operators to meet the ever increasing data traffic, solutions have to be found to try and reduce BS energy consumption to make the BSs more energy efficient and to reduce the mobile networks’ operational expenditure (OPEX) and carbon dioxide emissions. In this paper, a BS sleeping technology deployable in heterogeneous networks (HetNets) is proposed. The proposed scheme is validated by using extensive OMNeT++/SimuLTE simulations. From the simulations, it is shown that some lightly loaded micro BSs can be put to sleep in a HetNet when the network traffic is very low without compromising the QoS of the mobile network.

Cell Planning for Base Station in Mobile Communication Using an Improved Genetic Algorithm

2013 ◽  
Vol 284-287 ◽  
pp. 2699-2703 ◽  
Author(s):  
Hung Jen Liao ◽  
Chun Hung Richard Lin ◽  
Kuang Yuan Tung ◽  
Ying Chih Lin ◽  
Cheng Fa Tsai ◽  
...  
Keyword(s):  
Communication Networks ◽  
Mobile Communication ◽  
Mobile Networks ◽  
Base Station ◽  
Base Stations ◽  
Planning Problem ◽  
Improved Genetic Algorithm ◽  
Cell Planning ◽  
Planning Methods ◽  
The Cost

Cell planning problem is one of the most important issues in mobile communication networks. To tackle the problem, one should address the location management issue because it significantly affects the cost of cell planning in mobile networks. The partition of location areas is developed to minimize the total costs of considering user location and search operation simultaneously in cellular networks, which has been shown to be NP-complete and is commonly solved by metaheuristics in previous works. In this paper, we propose novel cell planning methods for base stations using genetic algorithms with initialization, local search, and particular mechanisms of area and cell crossovers. Several simulations are conducted on various cell networks with previous, random and real configurations. The simulation results reveal that our schemes are superior to the considered algorithms.

scholarly journals OVERVIEW OF OPTIMIZATION ALGORITHMS FOR UAVS POSITIONING

2021 ◽  
Vol 20 (4) ◽  
pp. 46-53
Author(s):  
Adrián STOSIL ◽  
◽  
Marcel VOLOŠIN ◽  
Taras MAKSYMYUK ◽  
Gabriel BUGÁR ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Base Station ◽  
Base Stations ◽  
System Capacity ◽  
End User ◽  
Widespread Application ◽  
High Bandwidth ◽  
Time Required ◽  
And Control ◽  
Different Levels

Mobile broadband networks can provide a reliable and flexible communication channel. User requirements can come with different levels of specificity. The widespread application of unmanned aerial vehicles (UAVs, commonly known as a drones) introduces possibilities of use in modern upcoming mobile networks; for example, 5G and 6G, to achieve and support various use cases from low latency to high bandwidth scenarios. For reliable command and control communication, mobile networks can provide flexible differentiated QoS matching the needed reliability, latency and throughput. Many end user equipment connected to the same base station can overload the system and may cause the network to be unavailable. Also, in case the fixed infrastructure is partially decommissioned, destroyed or the network is congested and the system capacity is not sufficient, it is appropriate to use autonomous drones as mobile base stations to ensure well signal coverage of the affected area. The aim of this work is to overview of optimization algorithm developed to provide the best drones’ locations. We compared the techniques of minimization of the number of drones needed to cover users located in a given area with respect to the time required to calculate the optimal positions of the drones.

scholarly journals User-Cell Association for Security and Energy Efficiency in Ultra-Dense Heterogeneous Networks

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 508
Author(s):  
Dania Marabissi ◽  
Lorenzo Mucchi ◽  
Simone Morosi
Keyword(s):  
Mobile Networks ◽  
High Speed ◽  
Minimum Energy ◽  
Base Station ◽  
Base Stations ◽  
Research Topics ◽  
Dense Networks ◽  
Digital Services ◽  
Exponential Increase ◽  
Cell Association

The last decades have been characterized by an exponential increase in digital services. The demand is foreseen to further increase in the next years, and mobile networks will have to mandatorily supply connections to enable digital services with very different requirements, from ultra high speed to ultra low latency. The deployment and the coexistence of cells of different size, from femto to macro, will be one of the key elements for providing such pervasive wireless connection: the ultra dense networks (UDN) paradigm. How to associate users and base stations is one of the most investigated research topics. Many criteria can be drawn, from minimization of power consumption to optimization of throughput. In this paper we propose a new utility to optimize two of the most important features of future mobile connection: security and energy consumption. By using our utility it is possible to jointly select the base station to be activated in a UDN, and associate users to the base stations with the aim of maximizing the secure throughput by spending the minimum energy. Moreover, we propose a heuristic that allows to achieve performance very close to the optimal one with reduced complexity. Effectiveness of the proposed approach is proved by means of comparison with benchmark approaches.

scholarly journals A Clustering-Driven Approach to Predict the Traffic Load of Mobile Networks for the Analysis of Base Stations Deployment

2020 ◽  
Vol 9 (4) ◽  
pp. 53
Author(s):  
Basma Mahdy ◽  
Hazem Abbas ◽  
Hossam Hassanein ◽  
Aboelmagd Noureldin ◽  
Hatem Abou-zeid
Keyword(s):  
Time Series ◽  
Mobile Networks ◽  
Time Series Data ◽  
Mobile Network ◽  
Base Station ◽  
Optimization Techniques ◽  
Base Stations ◽  
Traffic Load ◽  
Series Data ◽  
Better Than

Mobile network traffic is increasing in an unprecedented manner, resulting in growing demand from network operators to deploy more base stations able to serve more devices while maintaining a satisfactory level of service quality. Base stations are considered the leading energy consumer in network infrastructure; consequently, increasing the number of base stations will increase power consumption. By predicting the traffic load on base stations, network optimization techniques can be applied to decrease energy consumption. This research explores different machine learning and statistical methods capable of predicting traffic load on base stations. These methods are examined on a public dataset that provides records of traffic loads of several base stations over the span of one week. Because of the limited number of records in the dataset for each base station, different base stations are grouped while building the prediction model. Due to the different behavior of the base stations, forecasting the traffic load of multiple base stations together becomes challenging. The proposed solution involves clustering the base stations according to their behavior and forecasting the load on the base stations in each cluster individually. Clustering the time series data according to their behavior mitigates the dissimilar behavior problem of the time series when they are trained together. Our findings demonstrate that predictions based on deep recurrent neural networks perform better than other forecasting techniques.

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