scholarly journals Sdn in Edge Computing Based on Penguin Foraging Behaviour

2020 ◽  
Vol 9 (8) ◽  
pp. 34-37
Keyword(s):  
Foraging Behaviour ◽  
Search Algorithm ◽  
Base Station ◽  
Network Evolution ◽  
Small Cell ◽  
Edge Computing ◽  
Base Stations ◽  
High Coverage ◽  
A Cell ◽  
Small Base

Over the years usage of computational devices have been increased rapidly. 3G and 4G network evolution has helped in seamless usage of the modern devices. As the users are increasing rapidly and 4G spectrum is been congested way too fast. These situations resulted in development of 5G Spectrum by unlocking the millimetre waves. Milli meter Waves are originally shortrange waves and cannot be passed through heavy objects for these solution Small Base station concept has been implemented which provides high coverage and less latency while using. A small cell is basically a miniature base station that breaks up a cell site into much smaller pieces, and is a term that encompasses pico cells, micro cells, femto cells and can comprise of indoor/outdoor systems. For this implementation the SDN plays an important role for maintaining the connection between Base stations. Penguin foraging behaviour can be taken as a reference for the search algorithm in edge computing for getting faster results. Usually a penguin population comprises of several groups. Each group contains a number of penguins that varies depending on food availability in the corresponding foraging region. They feed as a team and follow their local guide which has fed on most food in the last dive. Similarly we follow the same process in small cell base station. Edge computing supports all devices simultaneous for processing and getting accurate results. They can be used for platform development for storage centric, server centric or even hybrid(storage-server) workloads.

scholarly journals User Association and Small-Cell Base Station On/Off Strategies for Energy Efficiency of Ultradense Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Jing Gao ◽  
Qing Ren ◽  
Pei Shang Gu ◽  
Xin Song
Keyword(s):  
Energy Efficiency ◽  
Optimization Method ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
User Association ◽  
User Mobility ◽  
Efficient Design ◽  
Widespread Application ◽  
Cell Base

The widespread application of wireless mobile services and requirements of ubiquitous access have resulted in drastic growth of the mobile traffic and huge energy consumption in ultradense networks (UDNs). Therefore, energy-efficient design is very important and is becoming an inevitable trend. To improve the energy efficiency (EE) of UDNs, we present a joint optimization method considering user association and small-cell base station (SBS) on/off strategies in UDNs. The problem is formulated as a nonconvex nonlinear programming problem and is then decomposed into two subproblems: user association and SBS on/off strategies. In the user association strategy, users associate with base stations (BSs) according to their movement speeds and utility function values, under the constraints of the signal-to-interference ratio (SINR) and load balancing. In particular, taking care of user mobility, users are associated if their speed exceeds a certain threshold. The macrocell base station (MBS) considers user mobility, which prevents frequent switching between users and SBSs. In the SBS on/off strategy, SBSs are turned off according to their loads and the amount of time required for mobile users to arrive at a given SBS to further improve network energy efficiency. By turning off SBSs, negative impacts on user associations can be reduced. The simulation results show that relative to conventional algorithms, the proposed scheme achieves energy efficiency performance enhancements.

scholarly journals Power density of rectangular microstrip patch antenna arrays for 5G indoor base station

2020 ◽  
Vol 19 (3) ◽  
pp. 1367
Author(s):  
Nor Adibah Ibrahim ◽  
Tharek Abd Rahman ◽  
Razali Ngah ◽  
Omar Abd Aziz ◽  
Olakunle Elijah
Keyword(s):  
Power Density ◽  
Antenna Arrays ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
System Capacity ◽  
High Data ◽  
Communication Devices ◽  
Set Up ◽  
Cell Base

The fifth-generation (5G) network has been broadly investigated by many researchers. The capabilities of 5G include massive system capacity, incredibly high data rates everywhere, very low latency and the most important point is that it is exceptionally low device cost and low energy consumption. A key technology of 5G is the millimeter wave operating at 28 GHz and 38 GHz frequency bands which enable massive MIMO and small cell base station densification. However, there has been public concern associated with human exposure to electromagnetic fields (EMF) from 5G communication devices. Hence, this paper studies the power density of a 5G antenna array that can be used for the indoor base station. The power density is the amount of power or signal strength absorbed by a receiver such as the human body located a distance from the base station. To achieve this, the design of array antennas using CST software at 28 GHz, fabrication and measurement were carried out in an indoor and hallway environment. The measurement processes were set up at IC5G at UTM Kuala Lumpur in which the distance of the transmitter to receiver where 1 m, 4 m, 8 m, and 10 m. In this study, the measured power density is found to be below the set limit by ICNIRP and hence no health implication is feared. Regardless, sufficient act of cautionary has to be applied by those staying close to small cell base stations and more studies are still needed to ensure the safety of use of 5G base stations.

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 Stochastic Geometry Analysis of Downlink Spectral and Energy Efficiency in Ultradense Heterogeneous Cellular Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jiaqi Lei ◽  
Hongbin Chen ◽  
Feng Zhao
Keyword(s):  
Energy Efficiency ◽  
Cellular Networks ◽  
Stochastic Geometry ◽  
Density Ratio ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
Heterogeneous Cellular Networks ◽  
Downlink Throughput ◽  
The Impact

The energy efficiency (EE) is a key metric of ultradense heterogeneous cellular networks (HCNs). Earlier works on the EE analysis of ultradense HCNs by using the stochastic geometry tool only focused on the impact of the base station density ratio and ignored the function of different tiers. In this paper, a two-tier ultradense HCN with small-cell base stations (SBSs) and user equipments (UEs) densely deployed in a traditional macrocell network is considered. Firstly, the performance of the ultradense HCN in terms of the association probability, average link spectral efficiency (SE), average downlink throughput, and average EE is theoretically analyzed by using the stochastic geometry tool. Then, the problem of maximizing the average EE while meeting minimum requirements of the average link SE and average downlink throughput experienced by UEs in macrocell and small-cell tiers is formulated. As it is difficult to obtain the explicit expression of average EE, impacts of the SBS density ratio and signal-to-interference-plus-noise ratio (SINR) threshold on the network performance are investigated through numerical simulations. Simulation results validate the accuracy of theoretical results and demonstrate that the maximum value of average EE can be achieved by optimizing the SBS density ratio and the SINR threshold.

scholarly journals Intelligent Resource Allocation Method for Wireless Communication Networks Based on Deep Learning Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hancheng Hui
Keyword(s):  
Resource Allocation ◽  
Communication Networks ◽  
Base Station ◽  
Resource Control ◽  
Network Throughput ◽  
Base Stations ◽  
Wireless Communication Networks ◽  
Mobile Location ◽  
Small Base ◽  
And Task

In this paper, a deep learning approach is used to conduct an in-depth study and analysis of intelligent resource allocation in wireless communication networks. Firstly, the concepts related to CSCN architecture are discussed and the throughput of small base stations (SBS) in CSCN architecture is analyzed; then, the long short-term memory network (LSTM) model is used to predict the mobile location of users, and the transmission conditions of users are scored based on two conditions, namely, the mobile location of users and whether the small base stations to which users are connected have their desired cache states, and the small base stations select the transmission. The small base station selects several users with optimal transmission conditions based on the scores; then, the concept of game theory is introduced to model the problem of maximizing network throughput as a multi-intelligent noncooperative game problem; finally, a deep augmented learning-based wireless resource allocation algorithm is proposed to enable the small base station to learn autonomously and select channel resources based on the network environment to maximize the network throughput. Simulation results show that the algorithm proposed in this paper leads to a significant improvement in network throughput compared to the traditional random-access algorithm and the algorithm proposed in the literature. In this paper, we apply it to the fine-grained resource control problem of user traffic allocation and find that the resource control technique based on the AC framework can obtain a performance very close to the local optimal solution of a matching-based proportional fair user dual connection algorithm with polynomial-level computational complexity. The resource allocation and task unloading decision policy optimization is implemented, and at the end of the training process, each intelligent body independently performs resource allocation and task unloading according to the current system state and policy. Finally, the simulation results show that the algorithm can effectively improve the quality of user experience and reduce latency and energy consumption.

scholarly journals Location-Based Resource Allocation in Ultra-Dense Network with Clustering

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4022
Author(s):  
Seong Jung Kim ◽  
Jeong Gon Kim
Keyword(s):  
Resource Allocation ◽  
Communication Systems ◽  
Base Station ◽  
User Equipment ◽  
Base Stations ◽  
System Capacity ◽  
Subcarrier Allocation ◽  
Dense Network ◽  
Small Base ◽  
Ultra Dense Network

With the rapid deployment of present-day mobile communication systems, user traffic requirements have increased tremendously. An ultra-dense network is a configuration in which the density of small base stations is greater than or equal to that of the user equipment. Ultra-dense networks are considered as the key technology for 5th generation networks as they can improve the link quality and increase the system capacity. However, in an ultra-dense network, small base stations are densely positioned, so one user equipment may receive signals from two or more small base stations. This may cause a severe inter-cell interference problem. In this study, we considered a coordinated multi-point scenario, a cooperative technology between base stations to alleviate the interference. In addition, to suppress the occurrence of severe interference at the cell edges, link formation was carried out by considering the degree of cell load for each cluster. After the formation of links between all the base stations and user equipment, a subcarrier allocation procedure was performed. The subcarrier allocation method used in this study was based on the location of base stations with clustering to improve the data rate and reduce the interference between the clusters. Power allocation was based on the channel gain between the base station and user equipment. Simulation results showed that the proposed scheme delivered a higher sum rate than the other resource allocation methods reported previously for various types of user equipment.

scholarly journals 5G Cellular Networks: Coverage Analysis in the Presence of Inter-Cell Interference and Intentional Jammers

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1538
Author(s):  
Muhammad Qasim ◽  
Muhammad Sajid Haroon ◽  
Muhammad Imran ◽  
Fazal Muhammad ◽  
Sunghwan Kim
Keyword(s):  
Cellular Networks ◽  
Orthogonal Frequency Division Multiplexing ◽  
Denial Of Service ◽  
Base Station ◽  
Base Stations ◽  
Network Coverage ◽  
Transmit Power ◽  
Coverage Analysis ◽  
Small Base ◽  
Inter Cell Interference

Intentional jammers (IJs) can be used by attackers for the launching of distributed denial-of-service attacks in 5G cellular networks. These adversaries are assumed to have adequate information about the network specifications, such as duration, transmit power and positions. With these assumptions, the IJs gain the ability to disrupt the legitimate communication of the network. Heterogeneous cellular networks (HetNets) can be considered a vital enabler for 5G cellular networks. Small base stations (SBSs) are deployed inside macro base station (MBS) to improve spectral efficiency and capacity. Due to orthogonal frequency division multiplexing assumption, HetNets’ performance is mainly limited by inter-cell interference (ICI). Additionally, there exist IJs-interference (IJs-I), which significantly degrades the network coverage depending on the IJs’ transmit power levels and their proximity with the target. The proposed work explores the uplink (UL) coverage performance of HetNets in the presence of both IJs-I and ICI. Moreover, to reduce the effects of ICI and IJs-I, reverse frequency allocation (RFA) is employed which is a proactive interference abating scheme. In RFA, different sub-bands of the available spectrum are used by MBS and SBS in alternate regions. The proposed setup is evaluated both analytically as well as with the help of simulation. The results demonstrate considerable UL coverage performance improvement by effectively mitigating IJs-I and ICI.

scholarly journals Sliding Window Based Feature Extraction and Traffic Clustering for Green Mobile Cyberphysical Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Jiao Zhang ◽  
Li Zhou ◽  
Angran Xiao ◽  
Sai Zeng ◽  
Haitao Zhao ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Control Strategies ◽  
Grid Method ◽  
Sliding Window ◽  
Base Station ◽  
Base Stations ◽  
Total Energy Consumption ◽  
High Coverage ◽  
Feature Extraction Method ◽  
Traffic Pattern

Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS) to handle this problem. In this paper, we propose a feature extraction method using sliding window to extract the distribution feature of mobile user equipment (UE), and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic clustering analysis to categorize collected traffic distribution samples into a limited set of traffic patterns, where the patterns and corresponding optimized control strategies are used to similar traffic distributions for the rapid control of base station state. Experimental results show that the sliding window is more superior in enabling higher UE coverage over the grid method. Besides, the optimized control strategy obtained from the traffic pattern is capable of achieving a high coverage that can well serve over 98% of all mobile UE for similar traffic distributions.

MEASUREMENT OF EMF EXPOSURE AROUND SMALL CELL BASE STATION SITES

2018 ◽  
Vol 184 (2) ◽  
pp. 211-215
Author(s):  
Marthinus Jacobus van Wyk ◽  
Jacobus Christiaan Visser ◽  
Christiaan Wynand le Roux
Keyword(s):  
Geographical Area ◽  
Mobile Network ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
Small Cells ◽  
Service Areas ◽  
Exposure Levels ◽  
Network Technologies ◽  
Cell Base

Abstract As mobile network technologies and usage change, mobile network cells have become smaller to meet the increased demand for data throughput. Small cell base stations are frequently used as a mobile network deployment method and are predominantly installed to service areas with a high density of people and to cover a small geographical area. Various measurement programs of the electromagnetic field (EMF) exposure have been conducted around base stations in general and these results have been published. There is, however, little data available on the EMF exposure levels around small cells. A measurement program was conducted to perform EMF exposure measurements around small cell base station sites. Results are compared to the relevant safety guidelines and to available data for EMF exposure around base stations in general.

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