Deployment Of Mobile Networks Research Articles

Mobile communication networks and Internet technologies as drivers of technical efficiency improvement

Empirical research on the determinants of technical efficiency (TE) is essential for policy formulation, in particular in low-income countries.In this study, we estimate the variations of TE between 1980 and 2009 in 23 low-income countries and 18 high-income countries, and demonstrate that TE has increased in both country groups in view of the deployment of mobile communication networks and Internet technologies. For low-income countries, we also prove that the causal relation is from the deployment of mobile networks and Internet technologies towards the increase of TE.More specifically, by estimating the stochastic production frontier for a flexible transcendental logarithmic production function under the assumption of fixed effects, we show that the increase in TE per additional mobile phone and Internet subscriber is the highest in Latin American and Asian countries, but the accrued TE increase in response to Internet usage is the largest in high-income countries due to an overly higher Internet diffusion.Having established that modern information and communication technologies improve the TE, we conclude discussing policies that lead to the spread of such technologies, particularly in low-income countries.

2G/3G connect: An educational software for teaching 2G/3G mobile communications to engineering students

AbstractMobile communications have become one of the key points in the development of Information Society. Therefore the market demands to qualify engineers with a good formation on this topic, and more specifically related with good knowledge about the design and deployment of mobile and wireless networks and services of different technologies. For this reason most of the graduate and post‐graduate programs in Electrical and Electronic engineering studies consider at least one specific subject focused on mobile communications. However, the large number of concepts and the different existing technologies could make this subject very difficult for the student. This article presents a software tool for the design of second and third generation radio access networks, which makes easier the understanding and application of theoretical concepts, giving the student a more practical and realistic view of the subject. Furthermore as this tool has been applied for the regulation on mobile communications in different countries, the students can get some practical knowledge about the work in mobile communications in real world applications. © 2012 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:1–12, 2015; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21570

Mobile network deployment under electromagnetic pollution control criterion: An evolutionary algorithm approach

Electromagnetic pollution due to mobile telephony is one of the most concerning problems arising since the spreading of this technology. Different studies have shown the relationship between continuous exposition to electromagnetic fields and different kinds of pathologies. Despite this, the electromagnetic danger for exposition is not taken into account in recent mobile network deployments. In this paper we propose a novel evolutionary algorithm for mobile networks deployment, which takes into account the control of the electromagnetic emission from the base stations as one of the key design parameters. The proposed evolutionary approach is a variable-length algorithm, able to produce solutions with different number of base stations. We detail the encoding, operators and a repairing procedure applied to obtain good solutions in terms of coverage, cost and electromagnetic pollution. The algorithm has been tested in a real problem of mobile network deployment in Alcalá de Henares, Madrid, Spain, and compare with a greedy (constructive) approach and a meta-heuristic algorithm (Harmony Search), obtaining very good results.

Dynamic Deployment of Wireless Sensor Networks by Biogeography Based Optimization Algorithm

As the usage and development of wireless sensor networks increases, problems related to these networks are becoming apparent. Dynamic deployment is one of the main topics that directly affects the performance of the wireless sensor networks. In this paper, biogeography-based optimization is applied to the dynamic deployment of static and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A binary detection model is considered to obtain realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the artificial bee colony algorithm, Homo-H-VFCPSO and stud genetic algorithm that are also population-based optimization algorithms. Results show biogeography-based optimization can be preferable in the dynamic deployment of wireless sensor networks.

Adaptive Communication-Constrained Deployment of Unmanned Vehicle Systems

Cooperation between multiple autonomous vehicles requires inter-vehicle communication, which in many scenarios must be established over an ad-hoc wireless network. This paper proposes an optimization-based approach to the deployment of such mobile robotic networks. A primal-dual gradient descent algorithm jointly optimizes the steady-state positions of the robots based on the specification of a high-level task in the form of a potential field, and routes packets through the network to support the communication rates desired for the application. The motion planning and communication objectives are tightly coupled since the link capacities depend heavily on the relative distances between vehicles. The algorithm decomposes naturally into two components, one for position optimization and one for communication optimization, coupled via a set of Lagrange multipliers. Crucially and in contrast to previous work, our method can rely on on-line evaluation of the channel capacities during deployment instead of a prespecified model. In this case, a randomized sampling scheme along the trajectories allows the robots to implement the algorithm with minimal coordination overhead.

Handover Call Admission Control for Mobile Femtocells with Free-Space Optical and Macrocellular Backbone Networks

The deployment of mobile femtocellular networks can enhance the service quality for the users inside the vehicles. The deployment of mobile femtocells generates a lot of handover calls. Also, numbers of group handover scenarios are found in mobile femtocellular network deployment. The ability to seamlessly switch between the femtocells and the macrocell networks is a key concern for femtocell network deployment. However, until now there is no effective and complete handover scheme for the mobile femtocell network deployment. Also handover between the backhaul networks is a major concern for the mobile femtocellular network deployment. In this paper, we propose handover control between the access networks for the individual handover cases. Call flows for the handover between the backhaul networks of the macrocell-to-macrocell case are proposed in this paper. We also propose the link switching for the FSO based backhaul networks. The proposed resource allocation scheme ensures the negligible handover call dropping probability as well as higher bandwidth utilization.

Design of Two-port MIMO Antennas without Space for Isolation

The deployment of mobile femtocellular networks can enhance the service quality for the users inside the vehicles. The deployment of mobile femtocells generates a lot of handover calls. Also, numbers of group handover scenarios are found in mobile femtocellular network deployment. The ability to seamlessly switch between the femtocells and the macrocell networks is a key concern for femtocell network deployment. However, until now there is no effective and complete handover scheme for the mobile femtocell network deployment. Also handover between the backhaul networks is a major concern for the mobile femtocellular network deployment. In this paper, we propose handover control between the access networks for the individual handover cases. Call flows for the handover between the backhaul networks of the macrocell-to-macrocell case are proposed in this paper. We also propose the link switching for the FSO based backhaul networks. The proposed resource allocation scheme ensures the negligible handover call dropping probability as well as higher bandwidth utilization.

MSNS: mobile sensor network simulator for area coverage and obstacle avoidance based on GML

Abstract A mobile sensor network is a distributed collection of sensors, each of which has sensing, computation, communication, and locomotion capabilities. In particular, locomotion facilitates the ability to self-deployment. In such a network of self-deployable mobile sensors, it is difficult to evaluate the effectiveness of mobile sensor network deployment in a given target area because we cannot predict the coverage rate for the target area. The coverage rate will be changed due to the number of sensor required in the target area, connectivity degree to be maintained and unknown obstacles. In this article, we develop mobile sensor network simulator (MSNS) in order to visualize (1) coverage secured by mobile sensors and (2) avoidance of obstacle objects (building, road and wall, and so on) on the real map drawn by GML (Geography Markup Language). From a user, MSNS receives the number of mobile sensor nodes, connectivity degree, sensor node's sensing range, communication range, and supersonic wave range. And then it visualizes the location information of sensor nodes, connectivity degree, and sensing coverage, all of which change with simulation time. Thereby we can estimate how many nodes are required in a given target area, and also calculate coverage rate of the target area in advance to the real deployment of mobile sensors.

Performance Evaluation Of Aodv, Dsr, Dsdv Mobile Ad-Hoc Protocols On Different Scenarios: An Analytical Review

A Mobile Ad-Hoc Network (MANET) [1][2][3][4][5][6][7] is a collection of wireless mobile nodes forming a temporary network without using any centralized access point or administration. MANET protocols have to face high challenges due to dynamically changing topologies, low transmission power and asymmetric links of network. A suitable and effective routing mechanism helps to extend the successful deployment of mobile ad-hoc networks. An attempt has been made to compare the performance of two On-demand reactive routing protocols namely AODV and DSR which works on gateway discovery algorithms and a proactive routing protocol namely DSDV which works on an algorithm to constantly update network topology information available to all nodes for MANETs on different scenarios. Comparison is made on the basis throughput, packet loss, packet delivery ratio and end-to-end delay, and the simulator used is NS-2 [2]. In the previous papers, only one type of scenario was taken while simulating the results. In our paper we have taken all the scenarios for simulation and then analyzed the results.

Entropy-Based Framework for Dynamic Coverage and Clustering Problems

We propose a computationally efficient framework to solve a large class of dynamic coverage and clustering problems, ranging from those that arise from deployment of mobile sensor networks to classification of cellular data for diagnosing cancer stages. This framework provides the ability to identify natural clusters in the underlying data set. In particular, we define the problem of minimizing instantaneous coverage as a combinatorial optimization problem in a Maximum Entropy Principle (MEP) framework that we formulate specifically for the dynamic setting, and which allows us to address inherent tradeoffs such as those between the resolution of the identified clusters and computational cost. The proposed MEP framework addresses both the coverage and the tracking aspects of these problems. Locating cluster centers of swarms of moving objects and tracking them is cast as a control design problem ensuring that the algorithm achieves progressively better coverage with time. Simulation results are presented that highlight the features of this framework; these results demonstrate that the proposed algorithm attains target coverage costs five to seven times faster than related frame-by-frame methods.

Artificial bee colony algorithm for dynamic deployment of wireless sensor networks

As the usage and development of wireless sensor networks increases, problems related to these networks are being discovered. Dynamic deployment is one of the main issues that directly affect the performance of wireless sensor networks. In this paper, an artificial bee colony algorithm is applied to the dynamic deployment of mobile sensor networks to gain better performance by trying to increase the coverage area of the network. The good performance of the algorithm shows that it can be utilized in the dynamic deployment of wireless sensor networks.

Radio Propagation Models for Mobile DTT Networks in the UHF Band

Este artículo estudia la idoneidad de diferentes modelos de propagación para despliegues de redes de Televisión Digital Terrestre (TDT) móvil sobre la banda de UHF. La precisión de los modelos de propagación de la señal es un aspecto clave para la planificación y minimización de costes de infraestructura de este tipo de redes, que se basan en estándares de radiodifusión tales como DVBT/ H, DVB-T2 o el futuro estándar para terminales móviles DVB-NGH. Este artículo analiza tres modelos de propagación: Okumura-Hata, Xia-Bertoni, un modelo basado en la fórmula de Hata que añade un término de difracción calculado usando el método de Deygout y el modelo COST 231 Walfisch-Ikegami. Para evaluar el rendimiento de los modelos se realizan campañas de medida sobre varios escenarios y con diferentes condiciones, como son la altura del transmisor, el entorno y los datos geográficos de los que se dispone. Por último se evalúa la variabilidad de la señal recibida en función del escenario, lo que supone un parámetro clave para un dimensionado de la red eficiente.

Optimizing Warehouse Forklift Dispatching Using a Sensor Network and Stochastic Learning

The authors report on a successful deployment of an inexpensive mobile wireless sensor network in a commercial warehouse served by a fleet of forklifts. The aim is to improve forklift dispatching and reduce the costs associated with the delays of loading/unloading delivery trucks. To that end, an integrated system including both hardware and software is constructed. First, the forklifts are instrumented with sensor nodes that collect an array of information, including the forklifts' physical location, usage time, bumping/collision history, and battery status. The hardware's capability is enhanced with a theoretically sound hypothesis testing technique to capture the rather elusive location information, and the collection of the data is done in an efficient event-driven manner. The information acquired combined with inventory information is fed into a sophisticated actor-critic type stochastic learning method to generate dispatching recommendations. Because noise is inevitable in such wireless sensor networks, the performance of the algorithm is investigated under different noise levels. In combining wireless sensing with state-of-the-art decision theory, this work extends beyond the standard use of wireless sensor networks as monitoring devices.

Efficient deployment of large mobile networks

The telecommunications industry has reached a phase of evolution where mobile communication networks are deployed in the growth market countries. New deployments are performed on an unforeseen scale involving installation of hundreds of base stations a day. The sheer volume of deployments in countries with less mature public infrastructure creates new operational challenges. One large issue at the start of the study was lengthy telecommunication implementation lead time (TILT). The cost of deployment is directly proportional to TILT. In this paper, the constraints of these large deployments were searched, listed and analyzed using the grounded analysis of a case study in India.

Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm.

As the usage and development of wireless sensor networks are increasing, the problems related to these networks are being realized. Dynamic deployment is one of the main topics that directly affect the performance of the wireless sensor networks. In this paper, the artificial bee colony algorithm is applied to the dynamic deployment of stationary and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A probabilistic detection model is considered to obtain more realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the particle swarm optimization algorithm, which is also a swarm based optimization technique and formerly used in wireless sensor network deployment. Results show artificial bee colony algorithm can be preferable in the dynamic deployment of wireless sensor networks.

SON Use Case Study “Energy Saving” for LTE eNBs

The 3GPP is defining a next generation radio access network called LTE (Long Term Evolution), which introduces several improvements respect current mobile systems, one of them are self-organization and self-optimization functions (SON) in base stations (eNB) and OM subsystem, that suppose a considerable increase on the network “intelligence”. This paper discusses the application of a SON function, Energy Saving, and evaluates the energy savings and system performance, when applied. To illustrate the effect of the energy saving techniques, several simulations have been carried out with a radio-planning tool in a real mobile network deployment. Two technical approaches have been followed: switching off cells and reducing the eNB transmitted power (TXP). For both approaches a reference scenario with 18 eNBs (with 54 cells) has been selected. This scenario reflects a dense urban area with a Manhattan like distribution, in an area of 2 km × 2 km, with an average ISD of 250 m. A 2×2 MIMO antenna configuration has been used in all simulations. eNB's transmitted power was 46 dBm, the operation frequency was 2 GHz and the bandwidth was 5 MHz. The Energy Saving is a promising SON Use Case that allows decreasing operator's energy costs, carbon footprint, and the radiation emitted by fixed infrastructure of the mobile telephony systems, such as base stations antennas.

Self-configuration and self-optimization for LTE networks

With the rapid growth of mobile communications, deployment and maintenance of cellular mobile networks are becoming more and more complex, time consuming, and expensive. In order to meet the requirements of network operators and service providers, the telecommunication industry and international standardization bodies have recently paid intensive attention to the research and development of self-organizing networks. In this article we first introduce both the market and technological perspectives for SONs. Then we focus on the self-configuration procedure and illustrate a self-booting mechanism for a newly added evolved NodeB without a dedicated backhaul interface. Finally, mobility load balancing as one of the most important selfoptimization issues for Long Term Evolution networks is discussed, and a distributed MLB algorithm with low handover cost is proposed and evaluated.

An energy-efficient dispersion method for deployment of mobile sensor networks

A novel method for deploying mobile sensors is proposed. The proposed method minimizes the energy consumption by deciding the target position before movement. It also deploys the sensor nodes in an optimal layout which provides maximum coverage and robust connectivity. To that end, we propose a novel topology, rake tree, in which each vertex can be matched to a position in the optimal layout. Simulation results show that the proposed method results in more coverage and consumes less energy compared to previous works.

Blackboard Mechanism Based Ant Colony Theory for Dynamic Deployment of Mobile Sensor Networks

A novel bionic swarm intelligence algorithm, called ant colony algorithm based on a blackboard mechanism, is proposed to solve the autonomy and dynamic deployment of mobiles sensor networks effectively. A blackboard mechanism is introduced into the system for making pheromone and completing the algorithm. Every node, which can be looked as an ant, makes one information zone in its memory for communicating with other nodes and leaves pheromone, which is created by ant itself in nature. Then ant colony theory is used to find the optimization scheme for path planning and deployment of mobile Wireless Sensor Network (WSN). We test the algorithm in a dynamic and unconfigurable environment. The results indicate that the algorithm can reduce the power consumption by 13% averagely, enhance the efficiency of path planning and deployment of mobile WSN by 15% averagely.

Joint Routing and Playout Buffering of IP Telephony Flows in MANETs

The low-cost of packet-based networking technologies with respect to traditional circuit-switched ones and the reliability of the current (wired) IP networks have brought to a considerable employment of the VoIP (Voice over IP) technologies in the voice services market. This success is expected to happen also in mobile ad hoc networks (MANETs), which may offer a good platform for the fast deployment of VoIP mobile networks. However, efforts must be made to improve performance before MANETs can be used for this purpose. One of the main limitations is related to the highly variability of the network topology and channel behavior, which heavily influences the service quality due to route losses and significant delay variations. In this paper, we propose a strategy where these impairments are jointly addressed. The source is responsible for jointly selecting the transmission paths and adjusting the playout delay, with an adaptive inter-talkspurt approach. These tasks are accomplished on the basis of historical data on network connectivity and transmission delays, and are driven by a quality-based approach. The collection of statistics of the network status relies on the QOLSR routing algorithm, whereas the voice quality is measured by means of the ITU-T E-Model.