Network Coverage Quality Research Articles

An Information Gradient Approach to Optimizing Traffic Sensor Placement in Statewide Networks

Traffic sensors are vital to the development and operation of Intelligent Transportation Systems, providing essential data for traffic monitoring, management, and transportation infrastructure planning. However, optimizing the placement of these sensors, particularly across large and complex statewide highway networks, remains a challenging task. In this research, we presented a novel search algorithm designed to address this challenge by leveraging information gradients from K-nearest neighbors within an embedding space. Our method enabled more informed and strategic sensor placement under budget and resource constraints, enhancing overall network coverage and data quality. Additionally, we incorporated spatial kriging analysis, harnessing spatial correlations of existing sensors to refine and reduce the search space. Our proposed approach was tested against the widely used Genetic Algorithm, demonstrating superior efficiency in terms of convergence time and producing more effective solutions with reduced information loss.

CONNECTING COMMUNITIES: ENHANCING BROADBAND ACCESS IN RURAL TANZANIA THROUGH SMALL CELL DEPLOYMENT

Aim: The aim of this study is to explores potential performance enhancement to a network infrastructure comprising with Macro-cells only by introducing and deploying cost-effective and adaptable small cell backhaul connections. For the marginalized rural areas and terrain varied areas, the aim is to explore how small cell deployment can bridge this gap and improve connectivity for underserved communities. Methodology: A framework is designed by leveraging LTE-Advanced features and integrating Macro cells and small cells in WinProp tool for wireless propagation and radio network planning. This proposed methodology is analysed through system simulations of a carefully selected practical deployment scenario in Southern Chunya, Tanzania. The path loss data of each pixel point in a study area is collected through this simulation study. The performance metrics of cellular signal transmission such as throughput, signal to interference noise ratio and spectral efficiency are examined through MATLAB tool. Results: The results illustrate that the deployment of small cells with LTE-Advanced features can enhance network coverage and overall quality, particularly in rural regions. The performance metrics of cellular signal transmission such as throughput, signal to interference noise ratio and spectral efficiency applied under this study have all shown improvement for a framework comprises with both macro cells and small cells as compared to a framework with Macro-cell alone. More over the results shows there is better results of throughput at 800MHz frequency band as compared to 2000MHz by little margin. The results were verified by conducting comparative assessment of similar studies. Conclusion The study has shown that small cells are potential for improving last mile connectivity and backhauling. The findings in this study will significantly guide future research and initiatives to bridge the digital divide and promote equitable access to broadband services in Tanzania and similar contexts worldwide.

Monitoring and control of smart urban drainage systems using NB-IoT cellular sensor networks.

Narrow-Band-Internet of Things (NB-IoT) is a promising wireless communication technology for harsh signal propagation conditions, including underground connectivity. The purpose of this study is to evaluate the real-life signal quality of an NB-IoT cellular sensor network for the monitoring and control of urban drainage systems. The implementation of the control systems toward smart infrastructures increase the need for low-cost and low-energy-consumption underground sensing devices. A measurement campaign was conducted in Rakvere, Estonia, to analyze the NB-IoT network's coverage and underground signal quality. The results were used to analyze the flood risk reduction potential in the pilot catchment, considering the quality of NB-IoT cellular network coverage. The signal measurements showed that in the case of plastic manholes, the best cellular transmitter placement is 0.5 m below the manhole cover, and at the ground level NB-RSRP reference signal strength of -104 dBm or better must be ensured to have a link budget with optimal energy consumption for communication. The results of flood risk reduction showed that excluding control locations with insufficient signal strength increased the number of major flooding nodes by 3.9% and mean flooding duration by 4.2% which is a relatively small change and characterizes the flexibility of the developed control system.

VKECE-3D: Energy-Efficient Coverage Enhancement in Three-Dimensional Heterogeneous Wireless Sensor Networks Based on 3D-Voronoi and K-Means Algorithm

During these years, the 3D node coverage of heterogeneous wireless sensor networks that are closer to the actual application environment has become a strong focus of research. However, the direct application of traditional two-dimensional planar coverage methods to three-dimensional space suffers from high application complexity, a low coverage rate, and a short life cycle. Most methods ignore the network life cycle when considering coverage. The network coverage and life cycle determine the quality of service (QoS) in heterogeneous wireless sensor networks. Thus, energy-efficient coverage enhancement is a significantly pivotal and challenging task. To solve the above task, an energy-efficient coverage enhancement method, VKECE-3D, based on 3D-Voronoi partitioning and the K-means algorithm is proposed. The quantity of active nodes is kept to a minimum while guaranteeing coverage. Firstly, based on node deployment at random, the nodes are deployed twice using a highly destructive polynomial mutation strategy to improve the uniformity of the nodes. Secondly, the optimal perceptual radius is calculated using the K-means algorithm and 3D-Voronoi partitioning to enhance the network coverage quality. Finally, a multi-hop communication and polling working mechanism are proposed to lower the nodes' energy consumption and lengthen the network's lifetime. Its simulation findings demonstrate that compared to other energy-efficient coverage enhancement solutions, VKECE-3D improves network coverage and greatly lengthens the network's lifetime.

IRS-Based UAV-Assisted Low-Altitude Passive Relaying: SER Performance Analysis of Optimal Deployment

This paper presents a method for analyzing the symbol error rate (SER) of a UAV cellular data network based on an IRS. This method can change the distances between the BS, IRS, UAV, and the elevation of the UAV to observe their impacts on the SER; then, a two-dimensional curve diagram of the parameters and the SER is drawn to determine the deployment position of the UAV. Finally, by flexibly changing the maximum angle of the UAV’s transmitted signal and the height of the UAV, the coverage area of the UAV’s cellular data network can be obtained through three-dimensional imaging, function fitting, and the extreme value of the condition function. As a relay of a cellular data network, a UAV can be flexibly deployed at any effective position at a low altitude to compensate for the limited coverage of the base station and the poor quality of the user’s received signal. In particular, an IRS deployed on the surface of a building can generate an equivalent line-of-sight channel to reflect the signal from the base station to the UAV. Using an IRS to change the signal phase and amplitude with the flexible deployment of UAVs can give priority to solving the problems of cellular data network coverage and signal quality in urban scenarios.

A comparative assessment of GSM and UMTS Networks

It is common knowledge that the transition of mobile networks from one generation to another is basically for the improvement in the network’s Quality of Service (QoS). Bearing this in mind, we will assumme that the Universal Mobile Telecommunication System (UMTS) will outperform the Global System for Mobile Communication (GSM), hence, the motivation to conduct this study in Calabar, Nigeria, for four mobile networks; MTN, Airtel, Globacom and 9mobile. With the aid of a TEMS investigation software installed in a laptop, a measurement campaign was carried out and log files collected, with focus on Call Setup Success Rate (CSSR), Dropped Call Rate (DCR), Handover Success Rate (HOSR), Call Setup Time (CST), network coverage and network quality. The collected data was analyzed with the aid of a TEMS discovery software. The analyzed data for each Key Performance Indicator (KPI) was compared with the minimum benchmark of the telecommunications regulatory body, the Nigerian Communication Commission (NCC). Result reveal that there was no outright improvement in the QoS and there was fluctuation in the QoS provided by the network operators. We therefore conclude that the network operators, either did not make accurate planning before installing their base stations or do not optimize their networks frequently and this led to poor QoS in most cases.

Challenges and Opportunities in Smart Antenna

The ever-increasing demand for larger bandwidth with seamless and fast data access for commuters resulted in developing new challenges for wireless service providers. With the increasing network mobility, the communication channel based characteristics between base stations and mobile users are changing rapidly. To meet these challenges, smart antennas have become an essential component in the emerging wireless systems. The increasing requirement for increasing stable network performance and reducing electromagnetic pollution has strengthened smart antenna adoption. The primary objective of this research study is to highlight current research works in the area of smart antennas by evaluating the key technologies, service strategies, solutions and its importance in terms of 5G including network coverage enhancement, data speed, and Quality of Service (QoS).

An Optimized Approach to Channel Modeling and Impact of Deteriorating Factors on Wireless Communication in Underground Mines.

The environment of underground coal mines has challenging properties that makes this zone inadaptable for a stable communication system. Additionally, various deteriorating physical parameters strongly affect the performance of wireless networks, which leads to limited network coverage and poor quality of data communication. This study investigates the communication capability in underground coal mines by optimizing the wireless link to develop a stable network for an underground hazardous environment. A hybrid channel-modeling scheme is proposed to characterize the environment of underground mines for wireless communication by classifying the area of a mine into the main gallery and sub-galleries. The complex segments of mine are evaluated by categorizing the wireless links for the line-of-sight (LOS) zones and hybrid modeling is employed to examine the characteristics of electromagnetic signal propagation. For hybrid channel modeling, the multimode waveguide model and geometrical optic (GO) model are used for developing an optimal framework that improves the accessibility of the network in the critical time-varying environment of mines. Moreover, the influence of various deteriorating factors is analyzed using 2.4 GHz to 5 GHz frequency band to study its relationship with the vital constraints of an underground mine. The critical factors such as path loss, roughness loss, delay spread, and shadow fading are examined under detailed analysis with variation in link structure for the mine.

Joint Deployment Strategy of Battery-Free Sensor Networks with Coverage Guarantee

The energy limitation of wireless sensors limits the lifetime of the traditional wireless sensor networks. The <b>Battery-Free Sensor Network (BF-WSN)</b> is a new network architecture proposed in recent years to address the limitation of wireless sensor networks. In a BF-WSN, the battery-free node can harvest energy from the ambient environment, and thus the lifetime of a BF-WSN is unlimited in terms of energy. The coverage quality is an important measurement of BF-WSNs. Considering the specific features of BF-WSNs, we propose a new deployment concept for BF-WSNs, named <i>Joint Deployment</i>. It aims to determine the locations and working schedules of sensor nodes to maximize network coverage quality. Based on the joint deployment concept, we propose a new deployment problem of battery-free sensor nodes. We prove that this problem is at least NP-Hard. We also analyze the upper bound of this problem. Furthermore, we propose an approximated algorithm to solve this problem and analyze the time complexity and the ratio bound of the algorithm. Extensive simulations are carried out to examine the performance of the proposed algorithm. The simulation results show that the algorithm is efficient and effective.

Intelligent User-Centric Networks: Learning-Based Downlink CoMP Region Breathing

In the presence of irregular transmission/reception point (TRP) topologies and non-uniform user distribution, the user-to-node association optimization is a rather challenging process in real user-centric networks, especially for the joint transmission aided coordinated multipoint (CoMP) technique. The grade of challenge further escalates, when taking the dynamic user scheduling process into account in order to enhance the system capacity attained. To tackle the above-mentioned problem, we holistically optimize the system by conceiving joint user scheduling and user-to-node association. Then, for the sake of striking a significantly better balance between the network capacity and coverage quality, we propose a generalized reinforcement learning assisted framework intrinsically amalgamated both with neural-fitted Q-iteration as well as with ensemble learning and transfer learning techniques. Consequently, a powerful policy can be found for dynamically adjusting the set of TRPs participating in the joint transmission, thus allowing the CoMP-region to breathe, depending on both the temporal and geographical distribution of the tele-traffic load across the network. To facilitate the prompt learning of the global policy supporting flexible scalability, the overall network optimization process is decoupled into multiple local optimization phases associated with a number of TRP clusters relying on iterative information exchange among them. Our simulation results show that the proposed scheme is capable of producing a policy achieving a network-edge throughput gain of up to 140%$ and a network capacity gain of up to 190% under the challenging scenario of having a non-uniform geographical UE distribution and bursty traffic.

An Elite Hybrid Particle Swarm Optimization for Solving Minimal Exposure Path Problem in Mobile Wireless Sensor Networks.

Mobile wireless sensor networks (MWSNs), a sub-class of wireless sensor networks (WSNs), have recently been a growing concern among the academic community. MWSNs can improve network coverage quality which reflects how well a region of interest is monitored or tracked by sensors. To evaluate the coverage quality of WSNs, we frequently use the minimal exposure path (MEP) in the sensing field as an effective measurement. MEP refers to the worst covered path along which an intruder can go through the sensor network with the lowest possibility of being detected. It is greatly valuable for network designers to recognize the vulnerabilities of WSNs and to make necessary improvements. Most prior studies focused on this problem under a static sensor network, which may suffer from several drawbacks; i.e., failure in sensor position causes coverage holes in the network. This paper investigates the problem of finding the minimal exposure paths in MWSNs (hereinafter MMEP). First, we formulate the MMEP problem. Then the MMEP problem is converted into a numerical functional extreme problem with high dimensionality, non-differentiation and non-linearity. To efficiently cope with these characteristics, we propose HPSO-MMEP algorithm, which is an integration of genetic algorithm into particle swarm optimization. Besides, we also create a variety of custom-made topologies of MWSNs for experimental simulations. The experimental results indicate that HPSO-MMEP is suitable for the converted MMEP problem and performs much better than existing algorithms.

Sensor Coverage Strategy in Underwater Wireless Sensor Networks

This paper mainly describes studies hydrophone placement strategy in a complex underwater environment model to compute a set of "good" locations where data sampling will be most effective. Throughout this paper it is assumed that a 3-D underwater topographic map of a workspace is given as input.Since the negative gradient direction is the fastest descent direction, we fit a complex underwater terrain to a differentiable function and find the minimum value of the function to determine the low-lying area of the underwater terrain.The hydrophone placement strategy relies on gradient direction algorithm that solves a problem of maximize underwater coverage: Find the maximize coverage set of hydrophone inside a 3-D workspace. After finding the maximize underwater coverage set, to better take into account the optimal solution to the problem of data sampling, the finite VC-dimension algorithm computes a set of hydrophone that satisfies hydroacoustic signal energy loss constraints. We use the principle of the maximize splitting subset of the coverage set and the ”dual” set of the coverage covering set, so as to find the hitting set, and finally find the suboptimal set (i.e., the sensor suboptimal coverage set).Compared with the random deployment algorithm, although the computed set of hydrophone is not guaranteed to have minimum size, the algorithm does compute with high network coverage quality.

Optimization of wireless network node deployment in smart city based on adaptive particle swarm optimization

In smart city wireless network infrastructure, network node deployment directly affects network service quality. This problem can be attributed to deploying a suitable ordinary AP node as a wireless terminal access node on a given geometric plane, and deploying a special node as a gateway to aggregate. Traffic from ordinary nodes is to the wired network. In this paper, Pareto multi-objective optimization strategy is introduced into the wireless sensor network node security deployment, and an improved multi-objective particle swarm coverage algorithm based on secure connection is designed. Firstly, based on the mathematical model of Pareto multi-objective optimization, the multi-target node security deployment model is established, and the security connectivity and node network coverage are taken as the objective functions, and the problems of wireless sensor network security and network coverage quality are considered. The multi-objective particle swarm optimization algorithm is improved by adaptively adjusting the inertia weight and particle velocity update. At the same time, the elite archive strategy is used to dynamically maintain the optimal solution set. The high-frequency simulation software Matlab and simulation platform data interaction are used to realize the automatic modeling, simulation analysis, parameter prediction and iterative optimization of wireless network node deployment in smart city based on adaptive particle swarm optimization. Under the premise of meeting the performance requirements of wireless network nodes in smart cities, the experimental results show that although the proposed algorithm could not achieve the accuracy of using only particle swarm optimization algorithm to optimize the parameters of wireless network nodes in smart cities, the algorithm is completed. The antenna parameter optimization process takes less time and the optimization efficiency is higher.

Trusted UAV Network Coverage Using Blockchain, Machine Learning, and Auction Mechanisms

The UAV is emerging as one of the greatest technology developments for rapid network coverage provisioning at affordable cost. The aim of this paper is to outsource network coverage of a specific area according to a desired quality of service requirement and to enable various entities in the network to have intelligence to make autonomous decisions using blockchain and auction mechanisms. In this regard, by considering a multiple-UAV network where each UAV is associated to its own controlling operator, this paper addresses two major challenges: the selection of the UAV for the desired quality of network coverage and the development of a distributed and autonomous real-time monitoring framework for the enforcement of service level agreement (SLA). For a suitable UAV selection, we employ a reputation-based auction mechanism to model the interaction between the business agent who is interested in outsourcing the network coverage and the UAV operators serving in closeby areas. In addition, theoretical analysis is performed to show that the proposed auction mechanism attains a dominant strategy equilibrium. For the SLA enforcement and trust model, we propose a permissioned blockchain architecture considering Support Vector Machine (SVM) for real-time autonomous and distributed monitoring of UAV service. In particular, smart contract features of the blockchain are invoked for enforcing the SLA terms of payment and penalty, and for quantifying the UAV service reputation. Simulation results confirm the accuracy of theoretical analysis and efficacy of the proposed model.

CMTN-SP: A Novel Coverage-Control Algorithm for Moving-Target Nodes Based on Sensing Probability Model in Sensor Networks.

The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy.

OPTIMASI NIRKABEL LOCAL AREA NETWORK FAKULTAS TEKNIK KAMPUS SUDIRMAN UNIVERSITAS UDAYANA

One of the changes in the field of telecommunications is the use of wireless technology. Wireless technology is applied to computer networks better known as Wireless Local Area Network (WLAN). Network coverage quality measurements can be seen from categories of delay or suspension, excess queues on the network, increased traffic, and output results. By using Wi-Fi Analyzer and Ekahau software we get the Quality of Service (QoS) value to see how good the coverage of the existing wireless network is. The result of the measurement is analyzed to get the adjustment of the wireless area coverage formula so that it can find the maximum range used as a reference in placing the ideal access point. The addition of access point points is done on all buildings where at some point the area can not be reached as a whole.

Design of Mobile Communication Indoor Distribution System

With the development of economy, the improvement of people's living standard has been increasing and theconstruction of buildings is becoming more demanding. These buildings are large in scale and of good quality andhave a strong shielding effect on mobile phone signals. In the middle of the large-scale buildings, undergroundshopping malls, underground parking and other environments, the mobile communication signal is weak hence thephone cannot be used normally and forming a mobile communication blind area and shadow area. In the middlefl oor, due to the surrounding diff erent base station signal overlap, the ping-pong eff ect, frequent switching of mobilephones and even dropped calls are seriously aff ecting the normal use of mobile phones. In the building's higher fl oors,due to the height of the base station antenna, it has abnormal coverage and there is also mobile communication blindspot. In addition, in some buildings, although the phone can answer normal call but the user density, base stationchannel congestion and mobile phone line is diffi cult. In particular, the network coverage, capacity and quality ofmobile communication are the key factors for operators to gain competitive advantage. Network coverage, networkcapacity and network quality fundamentally refl ects the mobile network service level and is the theme of all mobilenetwork optimization work. The indoor coverage system is produced under this background. According to the relevantstatistics in some areas of indoor traffi c in the total traffi c accounted for a higher proportion. Therefore, strengtheningthe indoor coverage is of great signifi cance to improve the quality of mobile communication.

Controllable Effective Threshold Based Fusion Coverage Algorithm in Mobile Sensor Networks

The coverage quality and network lifetime are two key parameters in the research of sensor networks. The coverage quality shows direct influences on the network lifetime. Meanwhile, it is influenced by many other factors such as physical parameters and environmental parameters. To reveal the connection between the coverage quality and the parameters of target node concerned, a fusion coverage algorithm with controllable effective threshold is proposed based on the sensing probability model. We give the model for the membership function of coverage intensity as well as the prediction model for the fusion operator. The range for the effective threshold is presented according to the membership function model. Meanwhile, the maximum of the effective coverage intensity for the target nodes within the monitoring area is derived. The derivation of the maximal fusion coverage intensity is elaborated utilizing a processing function on the distances from the target node to the ones in the sensor node set. Furthermore, we investigate different network properties within the monitoring area such as network coverage quality, the dynamic change of parameters, and the network lifetime, based on the probability theory and the geometric theory. Finally, we present numerical simulations to verify the performances of our algorithm. It is shown under different settings that, compared with the demand coverage quality, the proposed algorithm could improve the network coverage quality by 15.66% on average. The simulation experiment results show that our proposed algorithm has an average improvement by 10.12% and 13.23% in terms of the performances on network coverage quality and network lifetime, respectively. The research results are enlightening to the edge coverage and nonlinear coverage problems within the monitoring area.

Energy efficient network planning and dynamic control for hyper-cellular network

Hyper cellular network architecture is proposed to separate control coverage and traffic coverage, to realize flexible and energy-efficient network operations. Specifically, the traffic base stations (BSs), which only handle the data services, can be dynamically switched on/off and offload traffic to adjacent traffic base stations or control BSs for energy saving, according to the network load dynamics. With this new feature leveraged, it is crucial and challenging to revisit the problems of network planning, and dynamic BS sleeping and wireless resource allocation, based on the variation of the network traffic load. For the network planning, based on the stochastic geometry theory, the optimal densities of the control BSs and traffic BSs are derived, with respect to their different network functions and topology features. For energy efficient network control, dynamic BS sleeping and spectrum resource allocation mechanisms are proposed and optimized based on traffic offloading, which can substantially reduce the network energy consumption, with the guarantees on the network coverage and user quality of service.

Confident information coverage hole detection in sensor networks for uranium tailing monitoring

The wireless sensor networks recently abstract great attention and are used for a wide range of cyber-enabled applications each of which with rigid accuracy requirements. The emergence and existence of coverage holes in WSNs will dramatically degrade the network coverage performance and quality of service. To diminish the negative effects of coverage holes, this paper addresses and studies the confident information coverage hole detection problem (CICHD) based on the proposed novel confident information coverage model (CIC). For solving the CICHD problem, we design two effective heuristic CIC holes detection algorithms including the CHD without considering the nodes residual energy and the other CHDRE taking the nodes’ residual energy into account. In the both proposed algorithms, the sensing field is firstly partitioned into a series of reconstruction grids based on the spatial correlation and correlation range. Then each reconstruction grid will be scanned and detected based on the CIC model to be judged whether it is a hole. Once obtaining the coverage status of every reconstruction grid, the boundary of the coverage hole will be exacted by image processing method. The results of the simulations show that both the proposed schemes can efficiently detect the emerged coverage holes including the locations and the number, and the CHDRE algorithm is more practical and efficient compared to the CHD without considering the energy problem.