Low Network Coverage Research Articles

An improved bridge reference network for 3-D SAR tomography based on regional growing strategy

ABSTRACT The utilization of synthetic aperture radar tomography (TomoSAR) technology for the three-dimensional imaging of urban areas has garnered significant attention. In the case of multi-pass spaceborne TomoSAR, eliminating the atmospheric phase screen (APS) is a critical step. At present, a two-tier network method is widely employed for APS removal from extensive regions. However, challenges persist in the construction of first-tier reference networks using the Delaunay triangulation and bridge reference network methods, such as low network coverage ratios and linear correlation problems associated with near-parallel bridges. Consequently, a notable portion of the inversion results for buildings or artificial structures are either absent or characterized by low accuracy. To fully harness the observational information from all small connecting networks, this study introduces an improved bridge reference network construction method based on a region-growing strategy. This method merges small subnetworks with surrounding reference networks using high-quality bridge connections to maximize the coverage of the largest reference network. To validate the feasibility and effectiveness of the proposed approach, 27 TerraSAR-X images, which were collected in Shenzhen, China were utilized to construct a reference network and estimate building heights. The results clearly indicate that the proposed method effectively overcomes the limitations of existing methods.

A Novel Coverage Optimization Scheme Based on Enhanced Marine Predator Algorithm for Urban Sensing Systems

Ensuring the efficient operation of urban sensing systems under emergency conditions represents a current and significant challenge. To address the typical problem of low network coverage due to random deployment of wireless sensor network nodes in urban sensing systems, a novel coverage optimization scheme with an enhanced Marine Predator Algorithm (EMPA) is proposed. For a given target network monitoring area, a joint node sensing model based on Boolean sensing is constructed with the environmental information of the monitoring area as input, and then the model is optimized using EMPA for several iterations to obtain the optimized maximum network coverage and its corresponding optimal node location deployment scheme. Based on the standard MPA, firstly, the Tent chaotic map is introduced to initialize the population to maintain the population diversity of the algorithm; secondly, the adaptive jump step factor is introduced in the jump phase to improve the ability of the algorithm to jump out of the local optimum; finally, the double-subgroup location update strategy is introduced before the end of each iteration of the algorithm, which can better balance the local and global search and further enhance the algorithm’s optimal search capability. The algorithm is compared with four unimodal and multimodal benchmark test functions and applied to three network coverage optimization scenarios in urban sensing systems. The results show that the EMPA algorithm can efficiently optimize the network nodes’ uniform distribution, enhance average network coverage, and save a certain level of node deployment costs for urban sensing systems.

THE STUDENTS’ PERCEPTION OF THE APPLICATIONS USED IN ONLINE LEARNING DURING COVID-19 PANDEMIC AT BORNEO TARAKAN UNIVERSITY

This research aimed to describe students’ perception of efficient applications used in online learning at the English Education Department of Borneo Tarakan University. This research was quantitative research with 32 English Education respondents in the Borneo Tarakan University. The sampling method used was total sampling. The instrument used was a questionnaire. The results of the research indicated that the applications used in online learning amid the COVID-19 pandemic were very efficient because these applications provided a good way or alternative for supporting the learning activities from home. Students used various online learning applications. The applications used are considered efficient enough to help the learning process and can improve English skills, especially students’ speaking skills. Applications used during online learning also facilitate learning because of easy access in the low network coverage setting, not using too much internet bundlest, and economical and suitable enough features to support the learning process. Even though it supports the learning process, some students still find some difficulties with the applications used in online learning.

A sleep scheduling algorithm of redundant nodes in power communication sensor networks based on relative local density

In order to overcome the problems of low network coverage and short network node survival time in the traditional node sleep scheduling algorithm, a redundant node sleep scheduling algorithm based on relative local density is proposed in this paper. The composition of power communication sensor network is analysed, and the energy receiving model of redundant nodes in power communication sensor network is constructed. The sleep scheduling of network redundant nodes is realised according to the relative local density redundant node sleep algorithm. The results show that when the number of nodes is 120, the network performance of this method is 5.18 and the network coverage can reach 99.93%. At the same time, the survival time of sensor nodes under this method is longer, this method can prolong the network life cycle, and the sleep scheduling effect of redundant nodes is better.

The node deployment of wireless sensor networks based on mobile edge computing

When deploying network nodes, there are many redundant nodes, low network coverage and high energy consumption of network nodes, the node deployment method of wireless sensor networks(WSN) based on mobile edge computing is studied. WSN nodes are divided into anchor nodes and unknown nodes. Taking the location information of anchor nodes as a reference, the specific location of unknown nodes is obtained by trilateral measurement. Minimizing the node distance error is taken as the objective function, and the cuckoo search algorithm is used to solve it to obtain the final location result of the node. The mobile edge computing method is used to design the node deployment method of WSN to complete the node deployment. Simulation results show that the number of redundant nodes in this method is 3, maximum network coverage is 89%, maximum energy consumption of network nodes is 34.3J.

Benchmarking machine learning algorithms by inferring transportation modes from unlabeled GPS data

Many traffic-related applications, e.g. traffic demand modeling, rely on conventional data collection methods such as travel surveys. These methods can be demanding in terms of cost and time, which results in low network coverage and limited representativeness. On-motion sensors, e.g. smartphones, offer the opportunity to replace such methods and compensate for the aforementioned drawbacks by collecting positioning data automatically. GPS data consist of positioning records each of which has geographical coordinates and a timestamp associated. These data, however, require cleansing and processing before being put into use. Information about the used transportation mode is missing from this kind of data unless travelers were specifically asked to report it. In the literature, supervised machine learning (ML) algorithms were successful in inferring transportation modes from GPS data. However, these algorithms, unlike unsupervised ML algorithms, require training data that are not always available. This paper aims to investigate the capability of unsupervised ML algorithms to infer transportation modes from real GPS data extracted from smartphones. Therefore, we used two datasets to benchmark different unsupervised ML algorithms with different input attributes. The paper also investigates the feasibility of using a pre-trained model for unlabeled real data. Finally, we compared the best performing unsupervised setup to the supervised ML algorithms recommended in the literature. The results suggest that the recommended unsupervised setups can reach an overall inferring accuracy of 93%.

Descriptive analysis of routine childhood immunisation timeliness in the Western Cape, South Africa

Adherence to recommended age-specific immunisation schedules is critical in ensuring vaccine effectiveness against vaccine preventable diseases (VPDs). There is limited data on immunisation timeliness in sub-Saharan Africa. Therefore, this study assessed the timeliness of age-specific routine childhood immunisation within the Western Cape Province of South Africa. Participant records (N = 709) from a prospective health-facility based study conducted in Cape Town, SA in 2012–2016 were analysed. The outcome measure was receiving age-specific immunisations ≥4 weeks of that recommended for age as per the South African Expanded Programme on Immunisation (EPI-SA) schedule. Proportions, medians, inter-quartile ranges (IQR) and regression were used to obtain the prevalence, time-at-risk, and risk factors for delayed immunisation. A total of 652 /709 (91.9%) participants were eligible. Immunisation coverage declined with age from 94.9% (95% CI 92.9–96.4) at birth to 72.0% (95% CI 65.7–77.6) at 18 months. The highest delay in the uptake of vaccine doses was observed among the 3 rd dose of the DTP vaccine [163 (34.6% (95% CI 30.3–39.1)], while the lowest was seen among BCG [40 (6.5% (95% CI 4.7–8.8)]. The longest median time-at-risk of VPDs was among the 2 nd dose of the measles vaccine [12.9 (IQR 6.7–38.6) weeks] and the lowest was OPV birth dose [IQR 6.3 (5.3–9.1) weeks]. Low and upper-middle socio-economic quartiles were associated with delayed uptake of vaccine doses. Delayed vaccination increases the time of susceptibility to VPDs during infancy and childhood. There is a need to develop strategies aimed at mitigating factors associated with delay in uptake of routine childhood vaccines in the Western Cape. Mitigation strategies should provide vaccine education and mobile reminder systems. Education about timely vaccine uptake will aid in the provision of informed council from healthcare providers to caregivers. Multiple reminder systems could cater for low network coverage areas and caregivers with busy schedules.

SAT-CEP-monitor: An air quality monitoring software architecture combining complex event processing with satellite remote sensing

Air pollution is a major problem today that causes serious damage to human health. Urban areas are the most affected by the degradation of air quality caused by anthropogenic gas emissions. Although there are multiple proposals for air quality monitoring, in most cases, two limitations are imposed: the impossibility of processing data in Near Real-Time (NRT) for remote sensing approaches and the impossibility of reaching areas of limited accessibility or low network coverage for ground data approaches. We propose a software architecture that efficiently combines complex event processing with remote sensing data from various satellite sensors to monitor air quality in NRT, giving support to decision-makers. We illustrate the proposed solution by calculating the air quality levels for several areas of Morocco and Spain, extracting and processing satellite information in NRT. This study also validates the air quality measured by ground stations and satellite sensor data.

Temperature Compensation of Crystal References in NB-IoT Modems

The low-cost nature of NB-IoT modems encourages them to deploy uncompensated crystal oscillators (XOs) as frequency references. The frequency offset of an uncompensated XO, however, makes network acquisition inefficient under low network coverage. In the worst case, the bulk of an NB-IoT modem’s power is consumed in network acquisition. This work demonstrates a discrete frequency synthesizer prototype that employs its phase-locked loop to compensate for the frequency offset of its reference XO. We propose an accurate crystal model and a compensation logic that are suitable for 32-bit microprocessors, commonly available in NB-IoT modems. Alternatively, when synthesized in a commercial 65-nm process in 24-bit precision, the proposed compensation logic is simulated to require a total area of 0.029 mm2 and power of 290 nW at a refresh rate of 1.4 kHz. Moreover, the XO model requires only 0.16 kB of RAM. The prototype achieves a compensation error level of down to 27 ppb ( $3\sigma $ ) over the temperature range from −40 to 85 °C. The dominant error sources of the prototype are discussed in detail. In addition, we show that an NB-IoT modem can use the information acquired from sequential network acquisitions to compose and update its XO model in the field. This support for field calibration removes the need for XO characterization in production and ensures the validity of the model over the NB-IoT modem’s lifespan. The prototype achieves a compensation error level of down to 50 ppb ( $3\sigma $ ) in an emulated in-field calibration test, sufficient to ensure energy-efficient low-latency network acquisition under low network coverage.

Design and Implementation of MPVLC Li-Fi Model for End-To-End Wireless Data Transmission

Li-Fi system is a recent and brilliant technology which is utilized visible light as a medium for multimedia data transmission. In Li-Fi communication system, transfers data in the form of light signals as an alternative of Wi-Fi. The Li-Fi technology supports transmission of multimedia data in the way of light particles by sending the multimedia data via LED bulbs that make changes in faster transmission. The Li-Fi with hardware and software model creation with many parameters that must be considered while implementing a Li-Fi based transmission system prototype which is high data rate, distance and the LOS. These parameters are taken for major component when modelling a Light Fidelity system. The main problems in the implementation of an improved data rate at low network coverage and powerless location multi point VLC system and solar component are the range and cost effective model. The VLC source component and destination component must be compatible for high data rate. The conventional lighting technique in communication feels from intrusion and maximum delay possibilities. Solution for the above light based transmission problems in implementation; VLC is a preferred communication model because of its maximum throughput and secure transmission from light particles. The proposed Multi Point Visible Light Communication Li-Fi model provides high-speed communication to achieve better capacity, efficiency, and availability at low network coverage than existing lighting technology.

Perception of social media use in disseminating health-related academic information in public health schools in Minna, Nigeria

This study examined the use of social media among students at health schools in Minna to exchange health-related information. In order to obtain data from simple random samples of 344 respondents, the study used survey questionnaires. The rate of response was 100%. Findings found that the most used social media platforms for contact were Facebook (79.9%), WhatsApp (65.5%) and Twitter (34.3%). The research study also found that (79.8%) of student respondents benefited significantly from using social media to disseminate health-related information and preferred to communicate these health information through video, audio, and mobile phone text formats to them. The study concludes that low network coverage, high data subscription rates, high smartphone costs and epileptic power supply have an effect on access to social media at Minna health schools. The study recommended that lecturers, students, researchers and health care instructors should disseminate health related information using social media tools based on its effectiveness.

Perception of Social Media Use in Disseminating Health Related Academic Information in Public Health Schools in Minna, Nigeria

This study examined the use of social media among students at health schools in Minna to exchange health-related information. In order to obtain data from simple random samples of 344 respondents, the study used survey questionnaires. The rate of response was 100%. Findings found that the most used social media platforms for contact were Facebook (79.9%), WhatsApp (65.5%) and Twitter (34.3%). The research study also found that (79.8%) of student respondents benefited significantly from using social media to disseminate health-related information and preferred to communicate these health information through video, audio, and mobile phone text formats to them. The study concludes that low network coverage, high data subscription rates, high smartphone costs and epileptic power supply have an effect on access to social media at Minna health schools. The study recommended that lecturers, students, researchers and health care instructors should disseminate health related information using social media tools based on its effectiveness.

Anti-jamming method for vehicle communication network based on internet of vehicles technology

In order to solve the problems of poor signal anti-interference ability, high error rate and low network coverage in traditional vehicle communication network and improve the communication quality of vehicle communication network, an anti-interference method of vehicle communication network based on Internet of Vehicle (IoV) technology is proposed. The maximum cellular rate resource reuse algorithm (MCRRA) is used to optimise the link resources of vehicle communication network, so as to realise the optimal allocation of vehicle communication network resources. Then, the wavelet denoising method is used to filter the signal noise after resource allocation in vehicle communication network. Finally, the improved threshold function method of wavelet transform is used to compensate the pseudo-Gibbs phenomenon and signal loss in vehicle communication network. Experiments show that this method can effectively suppress the interference of vehicle communication network. The error rate of the vehicle communication network using this method is only 10%, and the coverage rate is as high as 98.7%.

Anti-jamming method for vehicle communication network based on internet of vehicles technology

In order to solve the problems of poor signal anti-interference ability, high error rate and low network coverage in traditional vehicle communication network and improve the communication quality of vehicle communication network, an anti-interference method of vehicle communication network based on Internet of Vehicle (IoV) technology is proposed. The maximum cellular rate resource reuse algorithm (MCRRA) is used to optimise the link resources of vehicle communication network, so as to realise the optimal allocation of vehicle communication network resources. Then, the wavelet denoising method is used to filter the signal noise after resource allocation in vehicle communication network. Finally, the improved threshold function method of wavelet transform is used to compensate the pseudo-Gibbs phenomenon and signal loss in vehicle communication network. Experiments show that this method can effectively suppress the interference of vehicle communication network. The error rate of the vehicle communication network using this method is only 10%, and the coverage rate is as high as 98.7%.

SECURED CAR HELPLINE NAVIGATION SYSTEM “CC HELPLINE”

There are several studies that have been implemented in the relation to navigation management system, most of which are research has done on the Secured Car Helpline navigation system. These studies have a mutual agreement with the motor insurance provider and service center provider that is highly dependent to ensure a good collaboration of business. One of the limitations that are gain from the proposed system is a collaboration between all the motor insurance agencies to gather the sufficient information to apply during the incident. In order to overcome the issue, the respective management members need to conduct a talk or speech with the respective representative of all motor insurance provider and service provider collaborate to make Secured Car Helpline navigation system “CC Helpline” more convenient. Hence, there is a certain location that has poor signals on the user’s device, where the respective user is unable to surf for a better connectivity in low network coverage areas. Not all the area has good strength connectivity, dead zones area considered due to limited access or no cellular connectivity. One of the ways of approaching this situation that is to get the better view of the issue, collaborating with Asia’s telecommunication such as Digi, Maxis, Celcom and U-Mobile to expand the network connectivity into unreachable areas and every user’s designated destination. As a proposed system, it has to develop as a live car helpline navigation system requires a good connectivity to the browser internet connection and a good network strength.

An Intervention to Improve Uptake of Referrals for Children with Ear Disease or Hearing Loss in Thyolo District, Malawi: Acceptability and Feasibility

(1) Introduction: Poor uptake of referral for ear and hearing services in Malawi has been demonstrated in previous research. A multi-component educational intervention was developed to address poor uptake. The aim of this study was to explore the feasibility and acceptability of the intervention. In addition, we aimed to provide a case study of an intervention development and feasibility testing process in preparation for a potential randomised trial. (2) Methods: The intervention included three components: (i) an information booklet; (ii) personalised counselling by a community health worker and an expert mother; (iii) a text message reminder. To assess feasibility, the counselling and information booklet were provided for caregivers of eligible children (<18 years) at ear and hearing outreach camps in Thyolo. Text message reminders were sent to caregivers after the camps. After 4 weeks, all caregivers were revisited and completed a structured questionnaire and a subset were interviewed in-depth. (3) Results: 30 children were recruited, and 53% took up the referral. Interviews found counselling with a booklet was acceptable. It provided motivation, enabled a two-way conversation, and helped dispel fear. It allowed information to be shared with social networks, initiating conversations about raising funds. The text message reminder was reported to be a valued prompt. Challenges to feasibility included low network coverage, and time needed for counselling. Residual barriers included the costs of transportation. The cost was £3.70/camp. (4) Conclusions: The study found that counselling with an information booklet was feasible and acceptable. The process of testing the feasibility of the intervention identified some adaptations to the intervention components and delivery which could be implemented before it is tested in a trial. This study highlighted the value of the feasibility testing process.

Studies on the Directivity of Horn Antennas for Communication Links in Low Network Coverage Areas

Studies on the Directivity of Horn Antennas for Communication Links in Low Network Coverage Areas

Factors influencing telecommunication subscribers’ decision to port among network providers in Nigeria.

Telecommunication subscribers’ retention and satisfaction are important goals for telecommunication network operators on their way to superior economic success in the liberalized Nigeria telecommunication market. The tight competition brought about by Mobile Number Portability(MNP) has resulted to the need for telecommunication service providers in Nigeria to constantly tune and fine-tune their marketing strategies to meet the dynamic behaviour and expectations of subscribers on quality service delivery. The Factors influencing telecommunication subscribers’ decision to port among network providers in Nigeria, Adopting a crosssectional survey design, a simple random sampling technique was used to enroll 378 subscribers of the four major network operators (MTN, Glo, Airtel, 9Mobile) aged 18–59 years and above residing in the three geopolitical zones (Owerri Municipal Orlu, and Okigwe) in Imo State into the study. Structured questionnaire was used for data collection, recorded significant facts in relation to subscribers’ decision to port among network providers. The hypothesis testing result of regression analysis using SPSS, a statistical software window version 21.0 to analyze and investigate the influence of Service quality, Network coverage, Call rate/tariff/price, Promotion, Customer care/ services as independent variables against the dependent variable confirmed that Service quality, Network coverage, Call rate/tariff/price, Promotion has significant influence on subscribers’ decision to port among network providers in Nigeria with significant levels less than 0.05 that is (0.000, 0.000, 0.014, 0.018) respectively. The factor identified as not having significant influence on subscribers’ decision to port is Customer care/services with significant levels greater than 0.05 that is 0.074. It is recommended that the network operators should assume the adequate control and management focus more on network extensions to various location where there is low network coverage, such that subscribers will be able to operate smoothly. It is also advised that more investment be made to enhance quality service delivery, and sustainable promotions, while also concentrating on price reduction both for data and call services as a way of increasing subscribers’ base.

Low SNR Uplink CFO Estimation for Energy Efficient IoT Using LTE

Machine Type Communications (MTC) is one of the prominent solutions to enable the Internet of Things (IoT). With a large number of IoT applications envisioned over the cellular network, the Third Generation Partnership Project (3GPP) has initiated the support for MTC in the Long Term Evolution (LTE)/ LTE-Advanced (LTE-A) standards. A significant portion of the MTC devices is expected to be low-complexity and low-power User Equipment (UE), requiring an energy efficient mode of operation. In addition, many such UEs can be located in the regions of low network coverage. In this paper, we show that an accurate estimation and compensation of the residual carrier frequency offset (CFO) at the base-station (eNB) results in a reduction in energy consumption for MTC devices in low coverage. For robust and accurate CFO estimation in low coverage, we propose a Maximum Likelihood (ML) based CFO estimation technique that works for data and/or pilot repetitions in LTE/LTE-A uplink. Through simulations, we illustrate that our technique shows a significant performance improvement over the conventional CFO estimation technique using the phase angle of the correlation between the repeated data. We determine that residual CFO estimation and compensation at the eNB results in 22.5%–55.2% reduction in energy consumption of the MTC devices, when compared to the case without CFO compensation.

A rule-based approach for determining the plausible universe of electric vehicle buyers in the Lisbon Metropolitan Area

The electric vehicle (EV) presents many advantages when compared to the internal combustion engine vehicle (ICEV): lower lifecycle energy consumption, operating costs, air and noise emissions. Conversely, it also has disadvantages: high purchase price, reduced driving range and insufficient charging system (long charging time and low network coverage). Car purchase behaviour is a well-studied process where explanatory models estimate the discrete choice probability of each alternative of the choice set based on car and consumers (socioeconomic) attributes.Differently, few studies have focused on the identification of the most plausible choice set depending on the individuals’ characteristics. This study aimed to evaluate the market potential of EV when such surveys are lacking, by identifying the households to whom the EV would be a plausible choice when buying a new car, despite its current cost and technological limitations. We developed a rule-based screening methodology where alternatives are eliminated from the consumer’s choice set using simple non-compensatory rules. In the end, we aim to obtaining a choice set that is closer to the real consumer’s choice set based on his socioeconomic traits and mobility patterns.After characterising households according to a set of 19 indicators (e.g., ‘Home location’, ‘Activity time’, ‘Daily trips’, etc.), they are classified according to 5 profiles that correspond to increasing probability of including an EV in their choice set. The latter two profiles delimit the potential market of EV. To accommodate the uncertainty regarding the future of EV related policies, four scenarios concerning different incentive policies were considered. This method was implemented in a case study in Lisbon Metropolitan Area, Portugal.Results suggest that, currently, the diffusion of EV in LMA is very restricted, ranging from 2% to 6.2% of the households, depending on the incentive policies. Even if the price of the EV was not a barrier, it would still be suitable only to 10.4% of the LMA households.