scholarly journals DDAS-DRoF Based a New In-Building Signal Coverage System Supporting Multiple Services

2017 ◽  
Vol 107 ◽  
pp. 558-563
Author(s):  
Jie Wang ◽  
Shulun Zhao ◽  
Xiaoguang Hu ◽  
Enyi Guan ◽  
Zhushun Ding ◽  
...  
Keyword(s):  
Signal Coverage ◽  
Multiple Services

Joint bandwidth and power allocation for multiple services in TV white space

2019 ◽  
Vol 13 (5) ◽  
pp. 569-577
Author(s):  
Zhong Tian ◽  
Jun Wang ◽  
Jintao Wang ◽  
Jian Song
Keyword(s):  
Power Allocation ◽  
White Space ◽  
Tv White Space ◽  
Multiple Services

scholarly journals Machine Learning and LPWAN Based Internet of Things Applications in Healthcare Sector during COVID-19 Pandemic

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1615
Author(s):  
Zeeshan Ali Khan ◽  
Ubaid Abbasi ◽  
Sung Won Kim
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
K Nearest Neighbors ◽  
Iot Applications ◽  
Processing Resources ◽  
Multiple Services ◽  
Applications Of Machine Learning

Low power wide area networks (LPWAN) are comprised of small devices having restricted processing resources and limited energy budget. These devices are connected with each other using communication protocols. Considering their available resources, these devices can be used in a number of different Internet of Things (IoT) applications. Another interesting paradigm is machine learning, which can also be integrated with LPWAN technology to embed intelligence into these IoT applications. These machine learning-based applications combine intelligence with LPWAN and prove to be a useful tool. One such IoT application is in the medical field, where they can be used to provide multiple services. In the scenario of the COVID-19 pandemic, the importance of LPWAN-based medical services has gained particular attention. This article describes various COVID-19-related healthcare services, using the the applications of machine learning and LPWAN in improving the medical domain during the current COVID-19 pandemic. We validate our idea with the help of a case study that describes a way to reduce the spread of any pandemic using LPWAN technology and machine learning. The case study compares k-Nearest Neighbors (KNN) and trust-based algorithms for mitigating the flow of virus spread. The simulation results show the effectiveness of KNN for curtailing the COVID-19 spread.

Simulation study of Multiple Services Ring (MSR)

2005 ◽  
Author(s):  
Zhanqi Xu ◽  
Shaohua Yu ◽  
Tao Yang ◽  
Jing Li
Keyword(s):  
Simulation Study ◽  
Multiple Services

A Customer-to-carrier Gateway for Multiple Services

1996 ◽  
Vol 6 (6) ◽  
pp. 312-326
Author(s):  
Elizabeth D. Zeisler ◽  
Daniel H. Bolton ◽  
Gordon B. Jones
Keyword(s):  
Multiple Services

Performance analysis of hybrid Fi-Wi network employing OCDMA based NG-PON

Frequenz ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Priyadharshini Rajasekaran ◽  
Geetha Ganesan ◽  
Meenakshi Murugappan
Keyword(s):  
Optical Network ◽  
High Capacity ◽  
Passive Optical Network ◽  
Error Vector Magnitude ◽  
Broadband Wireless ◽  
M Sequence ◽  
Integrated Architecture ◽  
Multiple Services ◽  
Code Division Multiple

Abstract Fiber-Wireless (Fi-Wi) networks play a crucial role in broadband wireless communication. A hybrid Fi-Wi architecture integrating Optical Code Division Multiple Access (OCDMA) based Next-Generation Passive Optical Network (NGPON) with Long Term Evolution (LTE) is proposed that can provide a higher capacity to the mobile end users, thereby achieving scalability and mobility. Maximal length sequence (M-sequence) codes of code length 31 used can support six users. A simulation study is carried out for the proposed integrated architecture considering multiple users and multiple services, and the performance is analyzed in terms of the received Bit Error Rate (BER) and Error Vector Magnitude (EVM) values. A high capacity of 160 Gbps and a spectral efficiency of 2–4 bps/Hz are achieved for the multi-user and multi-service links with six users.

scholarly journals Research on Distributed 5G Signal Coverage Detection Algorithm Based on PSO-BP-Kriging

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4390
Author(s):  
Tingli Xiang ◽  
Hongjun Wang
Keyword(s):  
Neural Network ◽  
Communication Network ◽  
Mobile Communication ◽  
Detection Algorithm ◽  
Base Station ◽  
Distributed Sensor ◽  
Mobile Communication Network ◽  
The Neural Network ◽  
Signal Coverage ◽  
5G Mobile Communication

In order to overcome the limitations of traditional road test methods in 5G mobile communication network signal coverage detection, a signal coverage detection algorithm based on distributed sensor network for 5G mobile communication network is proposed. First, the received signal strength of the communication base station is collected and pre-processed by randomly deploying distributed sensor nodes. Then, the neural network objective function is modified by using the variogram function, and the initial weight coefficient of the neural network is optimized by using the improved particle swarm optimization algorithm. Next, the trained network model is used to interpolate the perceptual blind zone. Finally, the sensor node sampling data and the interpolation estimation result are combined to generate an effective coverage of the 5G mobile communication network signal. Simulation results indicate that the proposed algorithm can detect the real situation of 5G mobile communication network signal coverage better than other algorithms, and has certain feasibility and application prospects.

scholarly journals Introduction to Containerization

2020 ◽  
Vol 6 (12) ◽  
pp. 294-300
Author(s):  
Raghav Goel and Dr. Bhoomi Gupta
Keyword(s):  
Large Scale ◽  
Software Engineer ◽  
Service Oriented Architecture ◽  
Use Case ◽  
Production Environment ◽  
Code Base ◽  
Enterprise Applications ◽  
Service Oriented ◽  
Multiple Services ◽  
Local Machine

Are you a software engineer/developer/coder or maybe even a tech enthusiast who is thinking of agility, parallel development and reducing cost. In the early twentieth century, we witnessed the rise of Service Oriented Architecture (SOA), which is a software architecture pattern that allows us to construct large-scale enterprise applications that require us to integrate multiple services, each of which is made over different platforms and languages through a common communication mechanism, where we write code and multiple services talk to each other’s for a business use case, but sometimes we end up with one big monolithic code base whose maintenance becomes difficult. Nowadays clients are using cloud and paying for on-demand services without effectively utilizing resources. These problems invite micro-services. In this paper, I am going to discuss how one should use scale application in a production environment and local machine

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