Nation-Wide Mobile Network Energy Evolution Analysis

A wireless ad hoc network is a decentralized type of wireless network. It is a type of temporary computer-to-computer connection. It is a spontaneous network which includes mobile ad-hoc networks (MANET), vehicular ad-hoc networks (VANET) and Flying ad-hoc networks (FANET). A MANET is a network that has many free or autonomous nodes often composed of mobile devices that can operate without strict top-down network administration [1]. A VANET is a sub form of MANET. It is a technology that uses vehicles as nodes in a network to create a mobile network. FANET is an ad-hoc network of flying nodes. They can fly independently or can be operated distantly. This paper discusses the characteristics of these three ad-hoc networks.

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SIMULASI NEURAL NETWORK UNTUK PREDIKSI LOKASI USER PADA MOBILE NETWORK

TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi Kendali Komputer Elektrik dan Elektronika ◽

10.25124/tektrika.v9i1.238 ◽

2016 ◽

Vol 9 (1) ◽

Author(s):

Alexander Driyarkoro ◽

Nurain Silalahi ◽

Joko Haryatno

Keyword(s):

Neural Network ◽

Mobile Station ◽

Mobile Network ◽

Learning Rate ◽

Noise Factor ◽

Optimal Learning ◽

Air Interface ◽

Location Area ◽

Optimal Learning Rate

Prediksi lokasi user pada mobile network merupakan hal sangat penting, karena routing panggilan pada mobile station (MS) bergantung pada posisi MS saat itu. Mobilitas MS yang cukup tinggi, terutama di daerah perkotaan, menyebabkan pencarian (tracking) MS akan berpengaruh pada kinerja sistem mobile network, khususnya dalam hal efisiensi kanal kontrol pada air interface. Salah satu bentuk pencarian adalah dengan mengetahui perilaku gerakan yang menentukan posisi MS. Dari MSC/VLR dapat diketahui posisi MS pada waktu tertentu. Karena location area suatu MS selalu unik dari waktu ke waktu, dan hal itu merupakan perilaku (behaviour) MS, maka dapat dibuat profil pergerakannya. Dengan menggunakan Neural Network (NN) akan diperoleh location area MS pada masa yang akan datang. Model NN yang digunakan pada penelitian ini adalah Propagasi Balik. Beberapa parameter NN yang diteliti dalam mempengaruhi kinerja prediksi lokasi user meliputi noise factor, momentum dan learning rate. Pada penelitian ini diperoleh nilai optimal learning rate = 0,5 dan noise factor = 1.

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Structural and evolution analysis of Cpz8, a primitive PAPS-dependent sulfotransferase

10.26226/morressier.5f6c5f439b74b699bf390b14 ◽

2020 ◽

Author(s):

Bruna Domingues Vieira

Keyword(s):

Evolution Analysis

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The Time Dependent Pricing (TDP) by Mobile Network Operators using Broad Band Pricing Systems

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v7i11.135140 ◽

2019 ◽

Vol 7 (11) ◽

pp. 135-140

Author(s):

Venugopal A. ◽

Niranchana D.

Keyword(s):

Broad Band ◽

Mobile Network ◽

Time Dependent ◽

Mobile Network Operators

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Mobile network synthesis strategy

Information and Control Systems ◽

10.31799/1684-8853-2019-1-98-101 ◽

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.

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