Station Placement Research Articles

ДЕРЖАВНЕ РЕГУЛЮВАННЯ РОЗМІРІВ САНІТАРНО-ЗАХИСНИХ ЗОН ПРИ РОЗМІЩЕННІ СУЧАСНИХ АВТОМОБІЛЬНИХ ЗАПРАВНИХ СТАНЦІЙ НА СЕЛЬБИЩНИХ ТЕРИТОРІЯХ

The work is devoted to the study of hygienic aspects of automobile filling station location in rural areas in modern conditions in order to minimize the negative impact of AFS on health and living conditions of the population. A theoretical generalization of the world experience of gas station design and operation was made. New data on the current ecological and hygienic state of design (location) of modern gas stations in Ukraine and their impact on the environment, health and living conditions of the population. Based on the materials of the work, the hygienic criteria for placing gas stations and their classification have been improved. Classification conditions for the definition of sanitary protection zones for gas stations of different capacity have been developed, which allowed to improve the legal and information-methodological base on hygiene planning and development of settlements in the design of gas stations of different types and capacities and develop a new SPZ standard for gas stations and filling stations. On the basis of the conducted researches the differentiated approach is offered and the procedure of the decision of questions concerning placement of gas stations in the territory of settlements is developed.

Optimal 3D UAV base station placement by considering autonomous coverage hole detection, wireless backhaul and user demand

The rising number of technological advanced devices making network coverage planning very challenging tasks for network operators. The transmission quality between the transmitter and the end users has to be optimum for the best performance out of any device. Besides, the presence of coverage hole is also an ongoing issue for operators which cannot be ignored throughout the whole operational stage. Any coverage hole in network operators' coverage region will hamper the communication applications and degrade the reputation of the operator's services. Presently, there are techniques to detect coverage holes such as drive test or minimization of drive test. However, these approaches have many limitations. The extreme costs, outdated information about the radio environment and high time consumption do not allow to meet the requirement competently. To overcome these problems, we take advantage of Unmanned aerial vehicle (UAV) and Q-learning to autonomously detect coverage hole in a given area and then deploy UAV based base station (UAV-BS) by considering wireless back-haul with the core network and users demand. This machine learning mechanism will help the UAV to eliminate human-in-the-loop (HiTL) model. Later, we formulate an optimisation problem for 3D UAV-BS placement at various angular positions to maximise the number of users associated with the UAV-BS. In summary, we have illustrated a cost-effective as well as time saving approach of detecting coverage hole and providing on-demand coverage in this article.

A Game Approach for Charging Station Placement Based on User Preferences and Crowdedness

The placement of electric vehicle charging stations (EVCSs), which encourages the rapid development of electric vehicles (EVs), should be considered from not only operational perspective such as minimizing installation costs, but also user perspective so that their strategic and competitive charging behaviors can be reflected. This paper proposes a methodological framework to consider crowdedness and individual preferences of electric vehicle users (EVUs) in the selection of locations for fast-charging stations. The electric vehicle charging station placement problem (EVCSPP) is solved via a decentralized game theoretical decision-making algorithm and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -means clustering algorithm. The proposed algorithm, referred to as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -GRAPE, determines the locations of charging stations to maximize the sum of utilities of EVUs. In particular, we analytically present that 50% of suboptimality of the solution can be at least guaranteed, which is about 17% better than the existing game theoretical based framework. We show a few variants to describe the utility functions that may capture the difference in preferences of EVUs. Finally, we demonstrate the viability of the decision framework via three real-world data-based experiments. The results of the experiments, including a comparison with a baseline method are then discussed.

Multilevel spatial impact analysis of high-speed rail and station placement: A short-term empirical study of the Taiwan HSR

Understanding the impact of high-speed rail (HSR) services on spatial distributions of population and employment is important for planning and policy concerning HSR station location as well as a wide range of complementary spatial, transportation, and urban planning initiatives. Previous research, however, has yielded mixed results into the extent of this impact and a number of influential factors rarely have been controlled for during assessment. This study aims to address this gap by controlling for socioeconomic and transportation characteristics in evaluating the spatial impacts of HSR (including station placement) at multiple spatial levels to assess overall impact across metropolitan areas. The Taiwan HSR is used for this empirical study. Research methods include descriptive statistics, multilevel analysis, and multiple regression analysis. Findings conclude that HSR-based towns, on average, may experience growing population and employment, but HSR-based counties are likely to experience relatively less growth of employment in the tertiary sector. HSR stations located in urban or suburban settings may have a more significant spatial impact. This differential in spatial change may be attributed to a high concentration of some subsectors and transportation services in the study area. Policy implications include adopting policies that encourage higher density at the local level, considering rural areas as a last choice for the installation of new HSR stations, and the use of HSR station placement to initiate brownfield urban regeneration in the urban core.

Electric vehicle charging strategy study and the application on charging station placement

Optimal placement of charging stations for electric vehicles (EVs) is critical for providing convenient charging service to EV owners and promoting public acceptance of EVs. There has been a lot of work on EV charging station placement, yet EV drivers’ charging strategy, which plays an important role in deciding charging stations’ performance, is missing. EV drivers make choice among charging stations according to various factors, including the distance, the charging fare and queuing condition in different stations etc. In turn, some factors, like queuing condition, is greatly influenced by EV drivers’ choices. As more EVs visit the same station, longer queuing duration should be expected. This work first proposes a behavior model to capture the decision making of EV drivers in choosing charging stations, based on which an optimal charging station placement model is presented to minimize the social cost (defined as the congestion in charging stations suffered by all EV drivers). Through analyzing EV drivers’ decision-making in the charging process, we propose a k-Level nested Quantal Response Equilibrium charging behavior model inspired by Quantal Response Equilibrium model and level-k thinking model. We then design a set of user studies to simulate charging scenarios and collect data from human players to learn the parameters of different behavior models. Experimental results show that our charging behavior model can better capture the bounded rationality of human players in the charging activity compared with state-of-the-art behavior models. Furthermore, to evaluate the proposed charging behavior model, we formulate the charging station placement problem with it and design an algorithm to solve the problem. It is shown that our approach obtains placement with a significantly better performance to different extent, especially when the budget is limited and relatively low.

Cost-Minimizing System Design for Surveillance of Large, Inaccessible Agricultural Areas Using Drones of Limited Range

Drones are used increasingly for agricultural surveillance. The limited flight range of drones poses a problem for surveillance of large, inaccessible areas. One possible solution is to place autonomous, solar-powered charging stations within the area of interest, where the drone can recharge during its mission. This paper designs and implements a software system for planning low-cost drone coverage of large areas. The software produces a feasible, cost-minimizing charging station placement, as well as a drone path specification. Multiple optimizations are required, which are formulated as integer linear programs. In extensive simulations, the resulting drone paths achieved 70–90 percent of theoretical optimal performance in terms of minimizing mission time for a given number of charging stations, for a variety of field configurations.

Investigating Transit-Induced Displacement Using Eviction Data

ABSTRACT This article uses eviction data to test the transit-induced displacement hypothesis—that the placement of new transit stations will lead to elevated property values, gentrification, and displacement. We use a case study of four cities in the United States that built or extended rail lines between 2005 and 2009: Newark, New Jersey; San Diego, California; Seattle, Washington; and St. Louis, Missouri. We employ a combination of propensity score matching and difference-in-differences modeling to compare eviction filing rates in gentrifiable neighborhoods near new transit stations with a set of similar neighborhoods not close to the station. We find very limited evidence that new transit neighborhoods experienced heightened rates of evictions compared with the controls. In three of the four cities, the effect of the opening of the station on eviction rates was insignificant. Eviction rates did spike in St. Louis immediately following the opening of the line, but this time period also coincided with the financial crisis.

Optimal placement of battery swap stations in microgrids with micro pumped hydro storage systems, photovoltaic, wind and geothermal distributed generators

The penetration of electric vehicles (EVs) in vehicle markets is increasing; however long charging time in battery charging stations is an obstacle for larger adoption of EVs. In order to address this problem, battery swap stations (BSSs) have been introduced to exchange near-empty EV batteries with fully charged batteries. Refilling an EV in BSS takes only a few minutes. With decentralization of power systems, BSSs are typically connected to the microgrid (MG) in their neighborhood. Although the location of BSS in MG affects MG operation cost, to the best knowledge of the author, optimal placement of BSS has not been done from the perspective of MG. Therefore, in this paper, the objective is to find optimal location of BSSs in a MG with micro pumped hydro storage (PHS), photovoltaic, wind and geothermal units, while reactive power dispatch and all network constraints are considered by AC optimal power flow. The effect of BSS capacity and maximum charging/discharging power, BSS to MG link capacity, PHS capacity and maximum power of PHS unit on MG operation and optimal BSS location are investigated. DICOPT solver in general algebraic mathematical system (GAMS) is used to solve the formulated mixed-integer nonlinear optimisation problem.

Multiple UAV-Mounted Base Station Placement and User Association With Joint Fronthaul and Backhaul Optimization

In this paper, we study a joint placement, resource allocation, and user association problem for UAV-assisted wireless networks with constrained backhaul links, where multiple UAV-mounted base stations (UBSs) are deployed to provide wireless services for ground users. We propose a novel framework to maximize the user throughput within the flight-time of UBSs and provides fairness among the users. We first obtain the optimal resource allocation schemes based on different fronthaul and backhaul conditions, and an efficient iterative algorithm is then developed to jointly optimize user association and UBS placement. The optimal UBS placement can be achieved by solving an unconstrained optimization problem which is a simplification of the initial constrained optimization problem based on the optimal resource allocation. We develop a dual-domain coordinated descent and bipartite graph matching based sub-process to identify an optimal user association that prefers the nearby UBSs, as the user association under constrained backhaul links have non-unique optimal solutions. Extensive simulations are conducted to verify the effectiveness of the proposed algorithm, and results show that our proposed method under constrained backhaul can improve both the average throughput by 49% and the fairness among the users by 47% in comparison with the method under ideal backhaul.

Agent-Based Modeling of Feeder-Level Electric Vehicle Diffusion for Distribution Planning

Faced with a rapidly growing electric vehicle (EV) load, distribution planners need a methodology to forecast when and where these loads will likely appear on specific distribution feeders. This paper proposes a new diffusion forecasting approach for residential EV and charging stations using agent-based modeling. Residential EV adoption is treated as a multi-criteria decision making problem modeled via analytic hierarchy process (AHP). The customer adoption model CANE is developed considering customer characteristics including car age, EV attractiveness valued using logistic regression, neighbor influences and customer economics. Distribution feeder topology is combined with property geographic information system (GIS) parcels and household travel survey data to determine geographic and electric locations for EV and charging stations. A Monte Carlo method is utilized to obtain the most likely outcome of the stochastic vehicle decision-making process and perform model calibration. The proposed diffusion forecasting approach is demonstrated using actual distribution feeder data. Using the diffusion results, EV impact on system annual peak, energy, losses, transformer aging and feeder upgrades is evaluated using quasi-static time-series power flow analysis. Case analyses are presented that examine the effect of EV price and charging station placement on EV diffusion and distribution feeder impact.

Genetic algorithm for biobjective optimization of indoor LTE femtocell deployment

SummaryThe optimization of indoor femtocell base stations (FBS) placement is a highly complex problem in which multiple performance figures can be considered. In this paper, we propose a biobjective optimization approach based on non‐dominated sorting genetic algorithm II (NSGA‐II) to solve the indoor FBS deployment problem in residential scenarios where a single cell is deployed within the coverage of a single dominant interfering external macro base station (MBS). The optimization problem is formulated with the objective of jointly minimizing outage probability and maximizing normalized downlink average throughput. Several conditions are simultaneously considered under the framework of Monte Carlo simulations, such as the effect of co‐channel interference in uplink and downlink, buildings with arbitrary layouts, realistic transmission schemes and antenna radiation patterns, random user distributions, and a well‐established empirical path loss model. The proposed algorithm, which determines the location and orientation of the FBS's antenna that provides a suitable compromise between the two objective functions, is evaluated in this paper. First, two different experiments are proposed to investigate the algorithm convergence; then, statistical analyses are formulated to characterize the relation between the values achieved for both objective functions; finally, the computational load is evaluated. Results indicate the convergence of the proposed method towards the real Pareto front and a significant reduction of the computational time with respect to a reference method based on exhaustive search, while pointing at new criteria for the selection of the objective functions.

On the 3-D Placement of Airborne Base Stations Using Tethered UAVs

One of the main challenges slowing the deployment of airborne base stations (BSs) using unmanned aerial vehicles (UAVs) is the limited on-board energy and flight time. One potential solution to such problem, is to provide the UAV with power supply through a tether that connects the UAV to the ground. In this paper, we study the optimal placement of tethered UAVs (TUAVs) to minimize the average path-loss between the TUAV and a receiver located on the ground. Given that the tether has a maximum length, and the launching point of the TUAV (the starting point of the tether) is placed on a rooftop, the TUAV is only allowed to hover within a specific hovering region. Beside the maximum tether length, this hovering region also depends on the heights of the buildings surrounding the rooftop, which requires the inclination angle of the tether not to be below a given minimum value, in order to avoid tangling and ensure safety. We first formulate the optimization problem for such setup and provide some useful insights on its solution. Next, we derive upper and lower bounds for the optimal values of the tether length and inclination angle. We also propose a suboptimal closed-form solution for the tether length and its inclination angle that is based on maximizing the line-of-sight probability. Finally, we derive the probability distribution of the minimum inclination angle of the tether length. We show that its mean value varies depending on the environment from 10° in suburban environments to 31° in high rise urban environments. Our numerical results show that the derived upper and lower bounds on the optimal values of the tether length and inclination angle lead to tight suboptimal values of the average path-loss that are only 0 - 3 dBs above the minimum value.

Optimization method of acoustic measurement station placement for wide-area miss distance

This paper focuses on the issue of how to select the optimal deployment scheme for the dispersal of miss distance during acoustic rendezvous measurements. Firstly, the measurement theory of acoustic rendezvous is introduced, and then the error model of acoustic rendezvous measurement is deduced and theoretical analysis is carried out. Then, an error evaluation index is established based on the dispersion characteristics of miss distance. Finally, simulation experiments are conducted for the miss distance obeying uniform distribution and normal distribution. Simulation experiments verify the correctness of the method in this paper, which has important guiding significance for the miss distance test.

Robust Planning and Operation of Multi-Cell Homogeneous and Heterogeneous Networks

In this work, we propose a robust planning tool that allocates power statically in homogeneous and heterogeneous cellular networks with non-regular base station (BTS) placement, to mitigate interference and improve overall performance. Each BTS will use the total available spectrum, but it will divide it into multiple sub-bands, and each BTS will transmit with a specific pre-computed power on each sub-band. We refer to such a power allocation as a power map . Our offline planning tool computes a robust power map for a given topology, by solving a non-convex, non-linear optimization problem, through simple transformations, based on geometric programming. The power map is computed based solely on the network topology, and it is made available to all BTSs that use it throughout the network operation to perform scheduling using a fast quasi-optimal online algorithm that we propose. We evaluate our planning tool for different homogeneous and heterogeneous networks (HetNets), first in a static setting where scheduling is performed optimally and then in a dynamic setting when scheduling is performed with our online scheduler. Results show that our solution significantly outperforms a classical equal power/fixed frequency reuse scheme in terms of sum-rate, by up to 30% in homogeneous networks and by up to 70% in HetNets.

Resource Allocation and 3-D Placement for UAV-Enabled Energy-Efficient IoT Communications

As the commercial launch of the fifth-generation (5G) wireless communications gets near, the trend from the Internet of Things (IoT) to the Internet of Everything (IoE) is emerging. Due to the advantages of the high mobility, high Line-of-Sight (LoS) probability and low labor cost, unmanned aerial vehicles (UAVs) may play an important role in the future IoT communication networks, e.g., data collection in remote areas. In this article, we study the 3-D placement and resource allocation of multiple UAV-mounted base stations (BSs) in an uplink IoT network, where the balanced task for the UAV-BSs, the limited channel resource, and the signal interference are taken into consideration. In the considered system, the total transmission power of IoT devices is minimized, subject to a signal-to-interference-and-noise ratio (SINR) threshold for each device. First, aiming to balance the task of each UAV, we propose a clustering algorithm based on an improved <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -means method to divide IoT devices into several groups so that the number of devices in each group is roughly the same. Then, based on matching theory, a modified-Hungarian-based dynamic many–many matching (HD4M) algorithm is designed for assigning subchannels to IoT devices, which can efficiently mitigate the interference. Finally, we jointly optimize the transmission power of IoT devices and the altitudes of UAVs via an alternating iterative method. The simulation results show that the total transmission power decreases significantly after applying the proposed algorithms.

LTE-Advanced Optimum Relay Placement with Zero Link Overflow Using AMMCS

Multi-hop Relay networks are proposed to fulfill the demanding coverage and capacity requirements for current applications in a cost efficient way. It can be used in IMT-Advanced technologies such as 3GPP LTE-Advanced. In this paper, Resource Blocks (RBs) proposed scheduling scheme is considered for zero multi-hop links overflow in Uplink LTE-Advanced. Then based on this scheduling scheme and other network assumptions the Optimum Relay Station (RS) placement in the cell was estimated using nonlinear optimization problem in order to improve LTE-A Uplink performance. The average throughput, Throughput gain, and Mean File Transfer Time (MFTT) are considered as performance measures. The study takes into consideration the impact of Asymmetry between multi-hop links, the effect of different arrival rates from random positions of UEs in the cell. Adaptive MIMO, Modulations, and Coding Switching (AMMCS) scheme is used to maximize network throughput with low bit error rate (BER). Simulation results show effective improvement in uplink network performance using the proposed scheduling scheme and AMMCS with RS at optimum location in the cell.

Developing GIS portal to ensure sanitary and epidemiological surveillance of transferring radio engineering objects

In recent years, in the Russian Federation there has been an increase in the levels of radiofrequency electromagnetic fields in residential areas, including due to an increase in the number of base stations (BS). The purpose of sanitary and epidemiological surveillance at the stages of placement and commissioning of base stations (BS) is to prevent their adverse effects on public health. The increase in the number of base stations, together with the advent of new electronic equipment and antennas, provide opportunities for improving the processes of their accounting at the stage of placement and monitoring of the levels of radiofrequency electromagnetic fields at the operation stage. This automation tool can be a geo-information portal for providing sanitary and epidemiological surveillance of cellular base stations. The prototype of the geo-information portal allows both calculating the size of sanitary protection zones (SPZ) and building restriction zones (RZ) from the BS in online mode, displaying the results of calculations in graphical form and issuing sanitary and epidemiological conclusions for the placement and operation of base stations. The geo-information portal has the ability to synchronize with the data of the radio frequency center. Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing will be able to receive up-to-date analytical data. There will be completely automated processes of collecting, processing and storing information on BS.

Developing GIS portal to ensure sanitary and epidemiological surveillance of transferring radio engineering objects

In recent years, in the Russian Federation there has been an increase in the levels of radiofrequency electromagnetic fields in residential areas, including due to an increase in the number of base stations (BS). The purpose of sanitary and epidemiological surveillance at the stages of placement and commissioning of base stations (BS) is to prevent their adverse effects on public health. The increase in the number of base stations, together with the advent of new electronic equipment and antennas, provide opportunities for improving the processes of their accounting at the stage of placement and monitoring of the levels of radiofrequency electromagnetic fields at the operation stage. This automation tool can be a geo-information portal for providing sanitary and epidemiological surveillance of cellular base stations. The prototype of the geo-information portal allows both calculating the size of sanitary protection zones (SPZ) and building restriction zones (RZ) from the BS in online mode, displaying the results of calculations in graphical form and issuing sanitary and epidemiological conclusions for the placement and operation of base stations. The geo-information portal has the ability to synchronize with the data of the radio frequency center. Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing will be able to receive up-to-date analytical data. There will be completely automated processes of collecting, processing and storing information on BS.

BIOLOGICAL EFFECTS AND LEGAL ASPECTS WHILE PLACING BASIC MOBILE COMMUNICATION STATIONS IN RESIDENTIAL AREAS OF SETTLEMENTS

The analysis of domestic standards for the placement of base stations of mobile communication systems in residential areas of settlements and the role of the public in making relevant decisions is carried out. Known studies of the effect of electromagnetic radiation on the health of people and experimental animals are considered. It was found that a long stay of living organisms in the zone of influence of base stations causes a number of negative biological effects. It is concluded that base stations should not be located directly within residential buildings, close to schools, healthcare facilities, parks and kindergartens.

Two-Year Observation of Fossil Fuel Carbon Dioxide Spatial Distribution in Xi’an City

The need for atmospheric carbon dioxide (CO2) reduction in the context of global warming is widely acknowledged by the global scientific community. Fossil fuel CO2 (CO2ff) emissions occur mainly in cities, and can be monitored directly with radiocarbon (14C). In this research, annual plants [Setaria viridis (L.) Beauv.] were collected from 26 sites in 2013 and 2014 in the central urban district of Xi'an City. The Δ14C content of the samples were analyzed using a 3 MV Accelerator Mass Spectrometer, and CO2ff concentrations were calculated based on mass balance equations. The results showed that the CO2ff mixing ratio ranged from 15.9 to 25.0 ppm (part per million, equivalent to μmol mol−1), with an average of 20.5 ppm in 2013. The range of measured values became larger in 2014, from 13.9 ppm to 33.1 ppm, with an average of 23.5 ppm. The differences among the average CO2ff concentrations between the central area and outer urban areas were not statistically significant. Although the year-to-year variation of the CO2ff concentration was significant (P < 0.01), there was a distinctly low CO2ff value observed in the northeast corner of the city. CO2ff emissions from vehicle exhaust and residential sources appeared to be more significant than two thermal power plants, according to our observed CO2ff spatial distribution. The variation of pollution source transport recorded in our observations was likely controlled by southwesterly winds. These results could assist in the optimal placement of regional CO2 monitoring stations, and benefit the local government in the implementation of efficient carbon emission reduction measures.