Cellular Towers Research Articles

Media Transmission by Cooperation of Cellular Network and Broadcasting Network

Future media transmission as a consistent target is pursued by both next mobile communication system (5G) and advanced digital terrestrial television system. High data rate and flexibility are major considerations for future media transmission. Broadcasting network facilitates high-efficiency transmission of popular or live video in large area, and while, cellular network tends to provide personalized and localized services with a unicast/multicast model. The broadcast-like scheme emerges in 5G to resolve the high demand for bandwidth. However, it requires high deployment cost and imposes much interference on unicast/multicast services. In this paper, a cooperative structure of cellular network and broadcasting network using cloud radio access network (C-RAN) is proposed. The expenses of constructing hybrid network can be significantly cut down by applying the centralization and virtualization of C-RAN. Besides, technical approaches for 3GPP and ATSC cooperation in physical layer is detailed. Dedicated return channel (DRC) of broadcasting network is proposed to enable seamless interaction between broadcasters and few users in a remote area with high expense of cellular tower deployment. To loosen the real-time physical layer pipes period restriction of DRC system, three alternative periods are investigated to provide more flexibility to broadcasters.

Verifiable and Privacy-preserving Check-ins for Geo-social Networks

Enabling efficient and accurate location verification is a desirable technique for the proliferation of many “check-in” based location sharing services. Existing solutions either use modified infrastructures, such as WiFi APs and cellular towers, to issue location proofs for users, which suffer from high infrastructure extension cost, or rely on co-located users to issue location proofs for each other, which are vulnerable to collusion attacks. In this paper, we propose a novel location verification approach that is based on the concept of location tag. When a user requests to check-in at certain venue, both the device of the user and of the venue will submit a location tag, which actually is a collection of environmental signals presented at a certain location and time, to the service provider. Based on the similarity of the two location tags, the service provider can verify whether the user is actually at the location as she claimed. Due to the high time- and space- dependence of environmental signals, it is hard for users to forge location tags. On the other hand, to protect privacy of a user from the location-sharing service, periodically changed pseudonyms are used by users when checking-in at venues, and partially blind signatures are employed by the services to issue check-in confirmation messages. Then users will submit the check-in confirmation messages in a batch manner, using their true Identities. Thus, the location-sharing service knows who has checked-in at which venue, but does not know when the user did. As a result, temporal privacy of user check-ins can be achieved. Thorough analysis and experiments are conducted to demonstrate the feasibility, security and efficiency of the proposed approach.

Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

Understanding mobile traffic patterns of large scale cellular towers in urban environment is extremely valuable for Internet service providers, mobile users, and government managers of modern metropolis. This paper aims at extracting and modeling the traffic patterns of large scale towers deployed in a metropolitan city. To achieve this goal, we need to address several challenges, including lack of appropriate tools for processing large scale traffic measurement data, unknown traffic patterns, as well as handling complicated factors of urban ecology and human behaviors that affect traffic patterns. Our core contribution is a powerful model which combines three dimensional information (time, locations of towers, and traffic frequency spectrum) to extract and model the traffic patterns of thousands of cellular towers. Our empirical analysis reveals the following important observations. First, only five basic time-domain traffic patterns exist among the 9600 cellular towers. Second, each of the extracted traffic pattern maps to one type of geographical locations related to urban ecology, including residential area, business district, transport, entertainment, and comprehensive area. Third, our frequency-domain traffic spectrum analysis suggests that the traffic of any tower among 9600 can be constructed using a linear combination of four primary components corresponding to human activity behaviors. We believe that the proposed traffic patterns extraction and modeling methodology, combined with the empirical analysis on the mobile traffic, pave the way toward a deep understanding of the traffic patterns of large scale cellular towers in modern metropolis.

CenLocShare: A centralized privacy-preserving location-sharing system for mobile online social networks

Friend relationships and location information are the biggest privacy concerns for the users in mobile Online Social Networks (mOSNs). Existing solutions save these two kinds of privacy information in two different servers, i.e., Social Network Server (SNS) and Location Based Server (LBS), and employ some encryption protocols to map each other to provide the location-sharing service among friends and strangers. However, this distributed architecture incurs large communication overhead between SNS and LBS, and great storage burden as well. In order to overcome these shortages, we propose a centralized privacy-preserving location-sharing system, named CenLocShare. It integrates SNS and LBS into one server, i.e., Location-storing Social Network Server (LSSNS), and uses the dummy locations and the dedicated mapping protocols between LSSNS and Cellular Tower (CT) to share privacy-preserving locations. Its safety is validated by the security analysis. Furthermore, we implement the prototype of CenLocShare and do some comparisons with other systems. The thorough experiments indicate our system decreases the query time for friends’ locations and the storage space CenLocShare is more suitable and effective in the context of mOSNs

ANALYSIS OF COLLAPSE METAL MAST COMMUNICATION

Ponte Academic JournalApr 2017, Volume 73, Issue 4 ANALYSIS OF COLLAPSE METAL MAST COMMUNICATIONAuthor(s): Garkin I.N.J. Ponte - Apr 2017 - Volume 73 - Issue 4 doi: 10.21506/j.ponte.2017.4.9 Abstract:Given the scenario of collapse of metal structures radio mast, analyzes the reasons for the fall and recommendations for operation of similar masts. This article was written based on a technical report on the identification of the causes of the collapse of a metal cellular tower in the Penza region in September 2015. Download full text:Check if you have access through your login credentials or your institution Username Password

Radiation Protection, Safety and Security Issues in Ghana

Although the use of radioisotopes in Ghana began in 1952, the Radiation Protection Board of Ghana was established in 1993 and served as the national competent authority for authorization and inspection of practices and activities involving radiation sources until 2015. The law has been superseded by an Act of Parliament, Act 895 of 2015, mandating the Nuclear Regulatory Authority of Ghana to take charge of the regulation of radiation sources and their applications. The Radiation Protection Institute in Ghana provided technical support to the regulatory authority. Regulatory and service activities that were undertaken by the Institute include issuance of permits for handling of a radiation sources, authorization and inspection of radiation sources, radiation safety assessment, safety assessment of cellular signal towers, and calibration of radiation-emitting equipment. Practices and activities involving application of radiation are brought under regulatory control in the country through supervision by the national competent authority.

Full On-Device Stay Points Detection in Smartphones for Location-Based Mobile Applications.

The tracking of frequently visited places, also known as stay points, is a critical feature in location-aware mobile applications as a way to adapt the information and services provided to smartphones users according to their moving patterns. Location based applications usually employ the GPS receiver along with Wi-Fi hot-spots and cellular cell tower mechanisms for estimating user location. Typically, fine-grained GPS location data are collected by the smartphone and transferred to dedicated servers for trajectory analysis and stay points detection. Such Mobile Cloud Computing approach has been successfully employed for extending smartphone’s battery lifetime by exchanging computation costs, assuming that on-device stay points detection is prohibitive. In this article, we propose and validate the feasibility of having an alternative event-driven mechanism for stay points detection that is executed fully on-device, and that provides higher energy savings by avoiding communication costs. Our solution is encapsulated in a sensing middleware for Android smartphones, where a stream of GPS location updates is collected in the background, supporting duty cycling schemes, and incrementally analyzed following an event-driven paradigm for stay points detection. To evaluate the performance of the proposed middleware, real world experiments were conducted under different stress levels, validating its power efficiency when compared against a Mobile Cloud Computing oriented solution.

Study of Power Density Transmitted from Cellular Base Station Towers of Nepal Telecom in Biratnagar Sub-Metropolitan City

Background: In this present world, human beings are being exposed directly or indirectly to some kind of ionizing and non-ionizing radiations with the development of recent scientific technologies or by natural phenomena. The study of the measurement of power density (PD) or Radio Frequency (RF) radiated from cellular Base Station Towers (BSTs) is seemed to be important in Nepal like other countries because of its various health effects. In this study, the authors measured the PD radiated from mobile base station towers in Biratnagar sub-metropolitan city, Morang. Methods and Methodology: All together 18 BSTs were selected within Biratnagar for the study purpose. Tenmars TM-196 which is a non-ionizing radiation detector was used to measure the power density. The Global Positioning System (GPS), a space-based satellite navigation system was used to locate the Maximum Peak Point (MPP) from the BSTs. Result: The maximum power density (PD) was observed near Jogbani boarder i.e. 3781.0 µW/m2 which was 0.63% of the NTA guidelines. Similarly, the minimum power density was observed near Rani BRT i.e 1549.3 µW/m2which was 0.26% of the NTA guidelines. Conclusion: From the survey it can be concluded that there is no significant health hazard to the general people due to non-ionizing radiation radiated from Base Station Towers in Biratnagar. Int J Appl Sci Biotechnol, Vol 4(3): 338-345

Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach

Understanding and forecasting mobile traffic of large scale cellular networks is extremely valuable for service providers to control and manage the explosive mobile data, such as network planning, load balancing, and data pricing mechanisms. This paper targets at extracting and modeling traffic patterns of 9,000 cellular towers deployed in a metropolitan city. To achieve this goal, we design, implement, and evaluate a time series analysis approach that is able to decompose large scale mobile traffic into regularity and randomness components. Then, we use time series prediction to forecast the traffic patterns based on the regularity components. Our study verifies the effectiveness of our utilized time series decomposition method, and shows the geographical distribution of the regularity and randomness component. Moreover, we reveal that high predictability of the regularity component can be achieved, and demonstrate that the prediction of randomness component of mobile traffic data is impossible.

Preliminary evidence suggesting that nonmetallic and metallic nanoparticle devices protect against the effects of environmental electromagnetic radiation by reducing oxidative stress and inflammatory status

IntroductionThere is increasing interest in evaluating the potential health risks and biologic effects of exposure to extremely low-frequency magnetic fields (ELF-MF) and electromagnetic radiation (EMR), like those associated with personal computers, cellular phones, and environmental radiation (e.g., cellular towers, high-voltage power lines, radar). ELF-MF may generate free radicals in biological organisms, which leads to hyperoxidative status. Here, we investigated the potential efficacy of protective devices constructed with nonmetallic and metallic nanoparticles, which are conductors and semiconductors of electromagnetic energy. MethodsIn a before and after study, 20 healthy subjects who regularly used cellular phones and were exposed to typical environmental EMF were given one of three different (ELF-MF) protective devices. Blood samples were drawn at baseline and one month after using the devices to examine redox and inflammatory status. ResultsWe found that, 30days after using the devices, plasma levels of lipid peroxidation, nitrites, and interferon-γ decreased significantly. Furthermore, the disulfide glutathione/glutathione ratio decreased, which indicated reduced intracellular oxidative damage. These data suggested that continuous use of devices that contain nonmetallic and metallic nanoparticles could protect healthy subjects from EMF-induced oxidative/inflammatory damage. ConclusionThus, for the first time, we have shown that the devices tested could be useful in counteracting the deleterious effects of EMF pollution by neutralizing harmful radiation before it reaches the body.

Mobile cellular big data: linking cyberspace and the physical world with social ecology

Understanding mobile big data, inherent within large-scale cellular towers in the urban environment, is extremely valuable for service providers, mobile users, and government managers of the modern metropolis. By extracting and modeling the mobile cellular data associated with over 9600 cellular towers deployed in a metropolitan city of China, this article aims to link cyberspace and the physical world with social ecology via such big data. We first extract a human mobility and cellular traffic consumption trace from the dataset, and then investigate human behavior in cyberspace and the physical world. Our analysis reveals that human mobility and the consumed mobile traffic have strong correlations, and both have distinct periodical patterns in the time domain. In addition, both human mobility and mobile traffic consumption are linked with social ecology, which in turn helps us to better understand human behavior. We believe that the proposed big data processing and modeling methodology, combined with the empirical analysis on mobile traffic, human mobility, and social ecology, paves the way toward a deep understanding of human behaviors in a large-scale metropolis.

Oorja unveils DMFC solution for telecom, stationary markets

Direct methanol fuel cell developer Oorja Protonics in California has announced its new Oorja Model T-1 fuel cell system, designed to provide a ‘green’ backup power solution for cellular telecom towers.

An Estimation of Electromagnetic Field Exposure from Cellular Mobile Base Station Towers in Densely Populated Residential Areas

An Estimation of Electromagnetic Field Exposure from Cellular Mobile Base Station Towers in Densely Populated Residential Areas

Landmarks based path planning for UAVs in GPS-denied areas∗∗This work is partially funded by FCT grant SFRH/BPD/103962/2014.

Abstract In this paper, we propose a UAV path planner travelling from a given source to goal location in GPS-denied areas. The environment consists of a set of cellular towers which are treated as landmarks having finite communication range. The vehicle has to perform dead reckoning in regions where landmarks are not available. Therefore, the objective is to determine a time optimal path taking the presence of landmarks into account while ensuring the covariance due to dead-reckoning is within a given bound. Solving the stochastic optimal control problem to determine a path in the continuous domain is very difficult and hence we discrete the path as a set of way points and optimize the location of these way points to obtain a time optimal path satisfying the covariance bounds. We use a particle swarm optimization technique coupled with a rabbit-carrot based path following technique to determine a near-optimal path. Numerical results are presented to show that our approach produces feasible paths that are near-optimal and satisfy the covariance bounds.

Cellpath: Fusion of cellular and traffic sensor data for route flow estimation via convex optimization

A new convex optimization framework is developed for the route flow estimation problem from the fusion of vehicle count and cellular network data. The issue of highly underdetermined link flow based methods in transportation networks is investigated, then solved using the proposed concept of cellpaths for cellular network data. With this data-driven approach, our proposed approach is versatile: it is compatible with other data sources, and it is model agnostic and thus compatible with user equilibrium, system-optimum, Stackelberg concepts, and other models. Using a dimensionality reduction scheme, we design a projected gradient algorithm suitable for the proposed route flow estimation problem. The algorithm solves a block isotonic regression problem in the projection step in linear time. The accuracy, computational efficiency, and versatility of the proposed approach are validated on the I-210 corridor near Los Angeles, where we achieve 90% route flow accuracy with 1033 traffic sensors and 1000 cellular towers covering a large network of highways and arterials with more than 20,000 links. In contrast to long-term land use planning applications, we demonstrate the first system to our knowledge that can produce route-level flow estimates suitable for short time horizon prediction and control applications in traffic management. Our system is open source and available for validation and extension.

A parallel algorithm for coverage optimization on multi-core architectures

Location siting is an important part of service provision, with much potential to impact operational efficiency, safety, security, system reliability, etc. A class of location models seeks to optimize coverage of demand for service that is continuously distributed across space. Decision-making and planning contexts include police/fire resource allocation for a community, siting cellular towers to support cell phone signal transmission, locating emergency warning sirens to alert the public of severe weather and other related dangers, and many others as well. When facilities can be sited anywhere in continuous space to provide coverage to an entire region, this is a very computationally challenging problem to solve because potential demand for service is everywhere and there are an infinite number of potential facility sites to consider. This article develops a new parallel solution approach for this location coverage optimization problem through an iterative bounding scheme on multi-core architectures. The developed approach is applied to site emergency warning sirens in Dublin, Ohio, and fire stations in Elk Grove, California. Results demonstrate the effectiveness and efficiency of the proposed approach, enabling real-time analysis and planning. This work illustrates that the integration of cyberinfrastructure can significantly improve computational efficiency in solving challenging spatial optimization problems, fitting the themes of this special issue: cyberinfrastructure, GIS, and spatial optimization.

Coverage Location Models

Achieving maximal coverage of service facilities has been of great interest to urban and regional planners. Examples include placing cellular towers, siting emergency response stations, and locating weather radars, among others. In some planning contexts, facilities could be sited almost anywhere in a region due to their small geographic footprints and demand is continuously distributed. This location problem has been represented as the continuous space maximal coverage problem (CSMCP). The CSMCP is widely acknowledged to be challenging to solve exactly. A broadly used solution approach for the CSMCP is to transform the problem into discrete maximal coverage models through continuous space discretization. A variety of discrete simplifications of CSMCP have been developed, attempting to address spatial representation issues that arise in the application of discrete models used as a continuous space approximation. However, the performance of applying these discrete coverage models to approximately solving the CSMCP has not been explicitly evaluated. It remains elusive as to which approach provides the best approximation for the CSMCP. This article therefore presents a comparative performance analysis of various discrete approximations for the CSMCP. Empirical results provide insights on how to achieve a balance between model representation detail and reasonable computation. Potential research directions are also suggested.

English

The massive increase of wireless communications in the world calls for responsible actions by governments in order to prevent possible health hazards. In addition to cellular towers overcrowding in urban areas, it is also important to consider other radio frequency radiations from different sources. The electric field intensity is one of the fundamental parameters to assess the exposure of human beings to Non-Ionizing Radiation (NIR). In this study, all main non-ionizing radiation sources in the urban area of Natal, Brazil (a city of about 860.000 inhabitants) were located and characterized with respect to frequency band, telecommunications service and integrated electric field strength. Measurements of far electric field intensity with frequency ranging from 30 MHz to 3 GHz were made in a survey of 140 outdoor points spread across all the 167.26 km2 area of the city. The results obtained have made it possible to draw a map of the regions of the city according to different electric field and exposure ratio (ER) intensities. In 71.4% of the sampled outdoor points, the highest exposure ratio measured were originated from TV broadcasting services, 22.1% from Transmissions Cellular Towers and 6.4% from Frequency Modulated Broadcasting. Key words: Non-ionizing radiation, electric field intensity, TV broadcasting, radio frequency radiation, measurement of radio frequency radiation, propagation in Urban Areas, International Commission on Non-Ionizing Radiation Protection (ICNIRP).

Cellpath: Fusion of Cellular and Traffic Sensor Data for Route Flow Estimation via Convex Optimization

A new convex optimization framework is developed for the route flow estimation problem from the fusion of vehicle count and cellular network data. The issue of highly underdetermined link flow based methods in transportation networks is investigated, then solved using the proposed concept of cellpaths for cellular network data. With this data-driven approach, our proposed approach is versatile: it is compatible with other data sources, and it is model agnostic and thus compatible with user equilibrium, system- optimum, Stackelberg concepts, and other models. Using a dimensionality reduction scheme, we design a projected gradient algorithm suitable for the proposed route flow estimation problem. The algorithm solves a block isotonic regression problem in the projection step in linear time. The accuracy, computational efficiency, and versatility of the proposed approach are validated on the I-210 corridor near Los Angeles, where we achieve 90% route flow accuracy with 1033 traffic sensors and 1000 cellular towers covering a large network of highways and arterials with more than 20,000 links. In contrast to long-term land use planning applications, we demonstrate the first system to our knowledge that can produce route-level flow estimates suitable for short time horizon prediction and control applications in traffic management. Our system is open source and available for validation and extension.

Location Based and Contextual Services Using Bluetooth Beacons: New Way to Enhance Customer Experience

 Abstract—Location based services and context enables innovative models of running business by adding tremendous value to the customers “in-location” experience and can extend the company’s digital interactions with the consumers. Indoor spaces often block cell signals and also make it nearly impossible to track customer’s indoor activities via existing technologies like GPS, RFID and Cellular tower triangulation etc.All these limitations in the existing technologies can be addressed using Bluetooth Beacons. Using beacons, retailers can optimize customer experiences, improve business processes and generate more revenue. Retailers and telecommunication service providers can do the partnerships with each other to rationalize customer experience and loyalty providing personalize offers and suggestions to loyal customers, empower sales associates and enhance in-store shopping experience of customer. Beacons have the ability to engage customers in the right place at the right time while offering utility and value. In this paper, authors have proposed, how Bluetooth beacons can be beneficial to retailers in terms of customer analytics, operational analytics and revenue improvement along with partnering with service providers to enhance customer experience and loyalty.