Base Station Sites Research Articles

Energy performance of off-grid green cellular base stations

The most energy-hungry parts of mobile networks are the base station sites, which consume around 60−80% of their total energy. One of the approaches for relieving this energy pressure on the electricity grid infrastructure and reducing the Operational Expenditures (OPEX) is to power base stations with renewable energy. However, the design of a green mobile network requires the dimensioning of the energy harvesting and storage systems through the estimation of the network’s energy demand. Therefore, this paper develops a diffusion-based modelling framework for solar-powered green off-grid base station sites. We apply this framework to evaluate the energy performance of homogeneous and hybrid energy storage systems supplied by harvested solar energy. We present the complete analysis, with numerical examples, to study the relationship between the design parameters and the energy performance metrics. The numerical computations demonstrate how the proposed framework can be applied to evaluate homogeneous and unconventional hybrid energy storage systems.

In Situ Assessment of Uplink Duty Cycles for 4G and 5G Wireless Communications.

In this presented study, we measured in situ the uplink duty cycles of a smartphone for 5G NR and 4G LTE for a total of six use cases covering voice, video, and data applications. The duty cycles were assessed at ten positions near a 4G and 5G base-station site in Belgium. For Twitch, VoLTE, and WhatsApp, the duty cycles ranged between 4% and 22% in time, both for 4G and 5G. For 5G NR, these duty cycles resulted in a higher UL-allotted time due to time division duplexing at the 3.7 GHz frequency band. Ping showed median duty cycles of 2% for 5G NR and 50% for 4G LTE. FTP upload and iPerf resulted in duty cycles close to 100%.

Research on Base Station Siting Method Based on 0-1 Planning Model and Immune Genetic Algorithm

With the rapid development of 5G technology, the high bandwidth required for communication shows a growing trend. However, the coverage area of the original base station gradually decreases, resulting in the expansion of the weak coverage area, in order to guarantee the quality and reliability of the communication network, there is an urgent need to establish new base stations in the weak coverage area. In this paper, a 0-1 planning model is developed with base stations and weak coverage points as the core elements. In this model, we aim to minimize the cost, and also consider the distance limitation and coverage demand, in order to ensure the premise of service demand, through the immunogenetic algorithm to achieve the optimization of the base station site selection. Ultimately, we have visualized it with the help of MATLAB to fully present the effectiveness and practical application value of this base station siting scheme.

Radio wave propagation analysis with dominant path model using MIMO antenna element for vehicular base station application

AbstractA low-profile slant ±45° polarized antenna for a 4G/5G base station with a dominant path wave propagation model (DPM) is reported in this paper. For dual-polarization and wide impedance bandwidth, the two dipole radiators are crisscrossed and a square metallic ring is integrated with the dipole arms and screwed with the four shorting vias. The antenna operates in Band 40/41/42/43 with strong isolation and low ECC (Envelop Correlation Coefficient). Fabricated antenna results show that the predicted wideband antenna has 13.38% bandwidth in 4G, which is Band 40/41, and 29.33% bandwidth in 5G sub-6 GHz Band 42/43. The antenna has a consistent radiation pattern, a 40 dB XPD (Cross Pol Discrimination), and a beam width of 69.5° ±1.5° in the entire frequency band. Three base station sites were explored to deploy the radiation pattern of a dual-polarized antenna in the 3D EM (Electromagnetic Analysis) tool. To evaluate signal quality, strength, radio network planning, and wave propagation analysis by analyzing antenna performance in real-time scenarios with 64 and 256 QAM (Quadrature Amplitude Modulation) techniques. For the proposed four-stream MIMO (Multiple-Input-Multiple-Output) antenna arrangement at deployed cell sites for 4G/5G base station applications, the maximum downlink and uplink data rates are 3.826/2.8 Mbps and 1044/800 Mbps respectively.

Statistical Characterization and Modeling of Indoor RF-EMF Down-Link Exposure

With the increasing use of wireless communication systems, assessment of exposure to radio-frequency electromagnetic field (RF-EMF) has now become very important due to the rise of public risk perception. Since people spend more than 70% of their daily time in indoor environments, including home, office, and car, the efforts devoted to indoor RF-EMF exposure assessment has also increased. However, assessment of indoor exposure to RF-EMF using a deterministic approach is challenging and time consuming task as it is affected by uncertainties due to the complexity of the indoor environment and furniture structure, existence of multiple reflection, refraction, diffraction and scattering, temporal variability of exposure, and existence of many obstructions with unknown dielectric properties. Moreover, it is also affected by the existence of uncontrolled factors that can influence the indoor RF-EMF exposure such as the constant movement of people and random movement of furniture and doors as people are working in the building. In this study, a statistical approach is utilized to characterize and model the total indoor RF-EMF down-link (DL) exposure from all cellular bands on each floor over the length of a wing since the significance of distance is very low between any two points on each floor in a wing and the variation of RF-EMF DL exposure is mainly influenced by the local indoor environment. Measurements were conducted in three buildings that are located within a few hundred meters vicinity of two base station sites supporting several cellular technologies (2G, 3G, 4G, and 5G). We apply the one-sample Kolmogorov-Smirnov test on the measurement data, and we prove that the indoor RF-EMF DL exposure on each floor over the length of a wing is a random process governed by a Gaussian distribution. We validate this proposition using leave-one-out cross validation technique. Consequently, we conclude that the indoor RF-EMF DL exposure on each floor over the length of a wing can be modeled by a Gaussian distribution and, therefore, can be characterized by the mean and the standard deviation parameters.

Research on Base Station Site Planning Based on Cluster Analysis and Azimuth Analysis Model

With the rapid development of the information age, the construction of 5G mobile network has improved the speed of network transmission and the utilization rate of spectrum. However, at the same time, the coverage of base stations is correspondingly less and less. In order to improve the quality of mobile communication, this paper uses the normal distribution 3-standard deviation method, Euclidean distance and 0-1 planning site selection model to analyze and divide the macro and micro base stations and make the optimal solution of site planning. Furthermore, the azimuth analysis model and K-means clustering algorithm were used to optimize the site planning and coverage area. Finally, 331 macro stations and 6459 micro base stations needed to be built, with an optimized Angle of 47 degrees and a coverage area of 93.3%. This paper provides some reference ideas for solving the problem of selecting and planning the base station site in the communication network.

Clustering Optimized Genetic Algorithm-Based 5G Communication base Station Site Selection

To minimize the negative impact of the base station construction, and at the same time make the base station cover as many users as possible, the Genetic Algorithm optimized Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is proposed. Initially, the number of points is fixed and encoded into a gene sequence with 4 different features at each point. After that, the process of the DBSCAN is stated and then it constructs the cluster adaptation function. Then, with the combination of the cluster adaptation function and the coverage function, it can select the individual, cross the gene sequence, and change the slight value of the sequence. Ultimately, by iteration, it can output the optimal point location and the result shows that the optimal coverage is 95%.

Разработка модели оптимизации выбора площадки базовой станции на основе алгоритма PMET-PSO

Existing research in the field of mathematical modeling of base station planning, using intelligent optimization algorithms to solve potential schemes for generating base station distributions, is complex and, for the most part, mathematical models for choosing a base station site require simplification. Also, the existing models for choosing the base station site solve the problem in two-dimensional space and do not take into account the influence of terrain and other factors. Having incorporated the concept of membrane computing into the basis of the MET-PSO algorithm, the PMET-PSO algorithm was developed. The PMET-PSO algorithm is a redesign of the METROPOLIS sample in the simulated annealing algorithm, projects the probability of accepting METROPOLIS in accordance with the number of iterations of the particle swarm algorithm and determines whether to obtain an individual optimal position and a global optimal position generated by a new round of iterations in accordance with probability, thereby adding randomness to the particle swarm algorithm. As the number of iterations increases, the randomness of the particle swarm algorithm decreases, and it converges to an optimal solution. PMET-PSO allows parallel computing, which effectively reduces the time complexity of the MET-PSO algorithm.

Passive UAV Tracking in Wireless Networks

Techniques for high accuracy tracking of the 3-D velocity, position, and cellular carrier frequency bias of unmanned aerial vehicles (UAVs) that communicate using a cellular network are presented. The tracking algorithm does <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">only</i> rely on asynchronous measurements of Doppler shift in a minimum of four base station sites. This number can be reduced to three, by combination with a round-trip time measurement from one site. The tracking is therefore independent of any capability of the UAV transceiver, like the global positioning system that may be disabled in the UAV by the pilot. Another significant advantage is that high precision time synchronization between base stations is not needed. The algorithm exploits interacting multiple model filtering, with the nonlinear measurement equations handled by extended Kalman filters. The low computational complexity, low sampling rate, and the uplink Doppler shift measurement resources enable joint tracking of several UAVs per cell. This makes the tracking technique relevant for supervision of UAV traffic using cellular connectivity, for example for border surveillance and surveillance of sensitive areas like airports where illegal flying may be extremely dangerous and costly. Theoretically, an observability analysis treats measurement configurations based on different combinations of Doppler shift and round-trip time. Simulations are used to illustrate the performance and to assess the initialization properties.

Uncoordinated Spectrum Sharing in Millimeter Wave Networks Using Carrier Sensing

We propose using Carrier Sensing (CS) for distributed interference management in millimeter-wave (mmWave) cellular networks where spectrum is shared by multiple operators that do not coordinate among themselves. In addition, even the base station sites can be shared by the operators. We describe important challenges in using traditional CS in this setting and propose enhanced CS protocols to address these challenges. Using stochastic geometry, we develop a general framework for downlink coverage probability analysis of our shared mmWave network in the presence of CS and derive the downlink coverage probability expressions for several CS protocols. Our work is the first to investigate and analyze (using stochastic geometry) CS for mmWave networks with spectrum and BS sites shared among non-coordinating operators. We evaluate the downlink coverage probability of our shared mmWave network using simulations as well as numerical examples based on our analysis. Our evaluations show that our proposed approach leads to an improvement in coverage probability, compared to the coverage probability with no CS, for higher values of signal-to-interference and noise ratio (SINR). Interestingly, our evaluations also reveal that for lower values of SINR, not using any CS is the best strategy in terms of the downlink coverage probability.

Mobile Communication Network Site Planning Research Based on Simulated Annealing Algorithm Optimization Model

With the development of 5G network, it becomes a hot topic to reasonably plan the siting of communication base stations in the weak coverage area of 5G network. In this paper, we take improving the coverage of service volume and reducing the cost of building base stations in the weak coverage area as the target of siting, and select base station sites among 2500×2500 points in a given area under ideal conditions and actual conditions, respectively, and use the less time-complex clustering method to cluster all weak coverage points. In order to improve the feasibility of the model in practical applications, we try to develop the base station site selection scheme that benefits the most for the 5G construction company by setting up a multi-objective planning model based on multiple constraints. On this basis, the conditions of the multi-objective planning model are changed and optimized to obtain a new multi-objective planning model based on the requirement that the communication coverage of base stations is fan-shaped in real life, and the simulated annealing optimization algorithm based on greedy thinking is used to optimize and solve the listed multi-objective planning model to obtain a new station site plan.

Study of 0-1 backpack planning based on simulated annealing algorithm and greedy algorithm for base station coverage and clustering problems

For the base station siting and planning problem in the communication industry, we first establish a 0-1 backpack dynamic planning model, and then use the simulated annealing algorithm and greedy algorithm to continuously optimize the base station sitting under different requirements. Moreover, the coverage area of the considered base stations is closer to the actual one (i.e., three sectoral areas). In this regard, we first establish the polar coordinate system to study the relationship between the change of the main direction angle of a single base station and the coverage area and then use the hierarchical clustering algorithm to classify the main direction angles of the three areas into three categories based on the distribution of weak coverage points around the stations and find the three best main direction angles of a single base station. And the greedy algorithm is used to solve the problem from local to overall so that each base station can cover the weakest coverage points as much as possible, and finally get a more ideal result that the total weak coverage rate of all base stations reaches 79.8%.

DIC-ST: A Hybrid Prediction Framework Based on Causal Structure Learning for Cellular Traffic and Its Application in Urban Computing

The development of technology has strongly affected regional urbanization. With development of mobile communication technology, intelligent devices have become increasingly widely used in people’s lives. The application of big data in urban computing is multidimensional; it has been involved in different fields, such as urban planning, network optimization, intelligent transportation, energy consumption and so on. Data analysis becomes particularly important for wireless networks. In this paper, a method for analyzing cellular traffic data was proposed. Firstly, a method to extract trend components, periodic components and essential components from complex traffic time series was proposed. Secondly, we introduced causality data mining. Different from traditional time series causality analysis, the depth of causal mining was increased. We conducted causality verification on different components of time series and the results showed that the causal relationship between base stations is different in trend component, periodic component and essential component in urban wireless network. This is crucial for urban planning and network management. Thirdly, DIC-ST: a spatial temporal time series prediction based on decomposition and integration system with causal structure learning was proposed by combining GCN. Final results showed that the proposed method significantly improves the accuracy of cellular traffic prediction. At the same time, this method can play a crucial role for urban computing in network management, intelligent transportation, base station siting and energy consumption when combined with remote sensing map information.

GTOOLS, an open-source MATLAB program for processing high precision, relative gravity data for time-lapse gravity monitoring

gTOOLS is an open-source software for the processing of relative gravity data. gTOOLS is available in MATLAB and as a compiled executable to be run under the free MATLAB Runtime Compiler. The software has been designed for time-lapse (temporal) gravity monitoring. Although programmed to read the Scintrex CG-5 and CG-6 gravimeters output data files, it can be easily modified to read data files from other gravimeters. The software binds together single-task processing modules within a very simple user interface that is based on one text file. Gravity processing involves three modules: (a) gravimeter calibration; (b) automatic processing of gravity data to find adjusted gravity differences; and (c) post processing of results. Each module is optional and runs independently from the others. Data processing includes (a) averaging out the measurements noise, and correction for solid Earth tides, and ocean loading, and residual instrumental drift, and (b) calculate the residual instrumental drift and gravity differences between the base station and monitoring sites, and their uncertainties, by a weighted least square analysis of the gravity data. The software allows the automatic processing of a gravity campaign spanning multiple days in a single run. The software is tested on gravity data from 2015 eruption at Cotopaxi volcano, Ecuador.

Coordinated Optimization for Energy Efficient Thermal Management of 5G Base Station Site

5G mobile communication system achieve better network performance while causing a significant increase in energy consumption, which hinders the sustainable development of the telecom industry. Even with many efforts for energy efficient system designs and equipment operation are developed, there is still a plenty of potential for energy savings in HVAC operation of 5G base station site since a significant amount of energy is consumed for thermal management by the HVAC system to control the indoor environment within an acceptable temperature range for safe and reliable operation of the base station (BS) equipment. In this work, a coordinated optimization approach for energy efficient thermal management of 5G BS site is proposed. The approach collaboratively optimized the HVAC system and the BS equipment with MILP model. The application results show that the average energy costs savings in HVAC operation with the coordinated approach are 24.8%-32.5%, and the total BS site costs savings are more than 13%.

UAV Base Station Site Selection Based on Spiral Algorithm in Complex Environment

The Wireless broadband communication system is the wireless communication hub and the main means of communication under the background of actual combat.In complex environments such as terrain impact and external interference strikes, the on-board base station of wireless broadband communication system may not work properly. As an air base station, UAV ensures the continuity and reliability of communication.Aiming at the problem of UAV base station location in complex environment, this paper proposes a UAV base station location method based on spiral algorithm.Firstly, this paper establishes the air-to-ground propagation model based on the characteristics of the actual geographical environment.Secondly, the coverage capability of the UAV base station is obtained by link budget and the optimal height analysis of the UAV.Finally, the location planning of the U AV base station is completed by the spiral algorithm. The simulation results show that the spiral algorithm needs fewer UAV base stations than the k-means algorithm, which can reduce the cost of the network. The method proposed in this paper can select the appropriate site for the base station of the UAV under the complex environment.

Design of station site selection for communication networks based on simulated annealing algorithm

With the development of the scale of mobile communication technology, the scale of operation and the bandwidth of communication are getting larger and larger, but the coverage of base stations is getting smaller and smaller. In order to minimize the cost of establishing base stations while covering a large amount of services, this paper uses objective planning and establishes a mathematical model to solve the optimal establishment method of base station siting. At the same time, the weak coverage points are clustered so that the weak coverage points can be managed among themselves effectively. Therefore, the improved simulated annealing algorithm is used to solve the problem. Firstly, the original data is pre-processed and the service volume of weak coverage points is sorted from largest to smallest, and the accumulated service volume of the first 35917 weak coverage points has reached 90% of the total service volume. In other words, it can be considered that the base stations are selected from this part of the points, and finally the optimal solution is obtained, when 90% of the total service volume is reached, the lowest accumulated cost of building base stations is 5705, and the coordinates of all new base stations and the type of base stations built are derived from this.

Analysis of greedy algorithm based base station siting search optimization

With the rapid development of 5G technology, the bandwidth of communication is increasing while the coverage of base stations is decreasing. Choosing a site for a mobile network, taking into account the coverage and cost of the base station, is a very challenging issue. When an area has weak coverage, it has an impact not only on the quality of the network, but also on the user experience. Therefore, the clustering of weak coverage points has to be continuously enhanced to facilitate the continuous development of mobile communication technology. This paper firstly establishes the optimization objective of finding large coverage with low station construction cost. Secondly, a greedy algorithm is used to calculate the optimal station site and the optimal sector angle to maximize coverage, taking into account two objective functions: cost and coverage, and to give an optimization scheme for the location of mobile communication network base stations.

Improving Hybrid Power Supply System for Telecommunication Service Providers in Nigeria

Abstract: The aim of this research is to use a combination of renewable energy sources and conventional diesel generator to model a cost effective, alternative energy source for telecommunication base stations in Nigeria. Actually, this study uses various theoretical and mathematical modelling tools, such as, Mat lab Simulink and HOMER software. In the same way, the study references several Base Transceiver Stations (BTS) from gsm providers at select geographical locations in Rivers State. The study references BTS infrastructure in locations such as Ogoni, Port Harcourt and Emohua. These locations were selected to reflect different climatic conditions in Rivers state. Against this background, various hybrid combinations comprising at least two sources of renewable energy e.g Wind Turbine generator(WTG) and Solar Photovoltaic (SPV) were modelled. Also, Fuzzy logic optimization algorithm was used in tracking the maximum power in the SPV. A sample Diesel Generator(DG) was studied to analyze which possible combination gives optimum performance and is most cost effective. The total cost for installation and maintenance of the hybrid system was also considered. Consequently, one of the common negative effects of conventional power generation and usage, which is environmental pollution, was also highlighted during the study. In the course of this research, Homer was used to model a hybrid system in which the initial capital Cost (ICC) was N101,517,040 for 96 nos battery, 1 no 10kw WTG, 1 no hydro-turbine, 48 nos converters, labour etc. The replacement cost for component has a depreciation of 30%; while maintenance for diesel is 30% of the ICC. Eventually, the results obtained from the simulations showed that with an increase in supply from renewable energy sources the overall cost spent when compared to using a diesel generator only is cut by 50%, while the pollution effects also dropped. In fact, the cost also reduces if the renewable energy system is designed efficiently to track and harness maximum power. Furthermore, it is also evident that the location of the base station site and the availability of Renewable energy source affects the efficiency and cost of the entire system. Hence, it is recommended that any telecommunication company which intends installing a hybrid power system for its base stations must carry out detailed feasibility studies using input parameters described here; especially, as it relates to siting of base stations in rural off-grid areas. Keywords: Hybrid Power Supply System

Dynamic Intervisibility Analysis of 3D Point Clouds

With the popularity of ground and airborne three-dimensional laser scanning hardware and the development of advanced technologies for computer vision in geometrical measurement, intelligent processing of point clouds has become a hot issue in artificial intelligence. The intervisibility analysis in 3D space can use viewpoint, view distance, and elevation values and consider terrain occlusion to derive the intervisibility between two points. In this study, we first use the 3D point cloud of reflected signals from the intelligent autonomous driving vehicle’s 3D scanner to estimate the field-of-view of multi-dimensional data alignment. Then, the forced metrics of mechanical Riemann geometry are used to construct the Manifold Auxiliary Surface (MAS). With the help of the spectral analysis of the finite element topology structure constructed by the MAS, an innovative dynamic intervisibility calculation is finally realized under the geometric calculation conditions of the Mix-Planes Calculation Structure (MPCS). Different from advanced methods of global and interpolation pathway-based point clouds computing, we have removed the 99.54% high-noise background and reduced the computational complexity by 98.65%. Our computation time can reach an average processing time of 0.1044 s for one frame with a 25 fps acquisition rate of the original vision sensor. The remarkable experimental results and significant evaluations from multiple runs demonstrate that the proposed dynamic intervisibility analysis has high accuracy, strong robustness, and high efficiency. This technology can assist in terrain analysis, military guidance, and dynamic driving path planning, Simultaneous Localization And Mapping (SLAM), communication base station siting, etc., is of great significance in both theoretical technology and market applications.