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Journal articles on the topic 'Cellular Network Positioning'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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1

Chai, Meiling, Changgeng Li, and Hui Huang. "A New Indoor Positioning Algorithm of Cellular and Wi-Fi Networks." Journal of Navigation 73, no. 3 (2019): 509–29. http://dx.doi.org/10.1017/s0373463319000742.

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Fluctuation of the received signal strength (RSS) is the key performance-limiting factor for Wi-Fi indoor positioning schemes. In this study, the Manhattan distance was used in the weighted K-nearest neighbour (WKNN) algorithm to improve positioning accuracy. Reference point (RP) intervals were optimised to reduce the complexity of the system. Specifically, two new positioning schemes are proposed in this paper. Scheme 1 uses the cellular network to refine the fingerprint database, while Scheme 2 uses the cellular network positioning to locate the node a priori, then uses the Wi-Fi network to

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Santa, José, Pedro J. Fernández, Ramon Sanchez-Iborra, Jordi Ortiz, and Antonio F. Skarmeta. "Offloading Positioning onto Network Edge." Wireless Communications and Mobile Computing 2018 (October 23, 2018): 1–13. http://dx.doi.org/10.1155/2018/7868796.

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While satellite or cellular positioning implies dedicated hardware or network infrastructure functions, indoor navigation or novel IoT positioning techniques include flexible storage and computation requirements that can be fulfilled by both end-devices or cloud back-ends. Hybrid positioning systems support the integration of several algorithms and technologies; however, the common trend of delegating position calculation and storage of local geoinformation to mobile devices or centralized servers causes performance degradation in terms of delay, battery usage, and waste of network resources.

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Brunello, Andrea, Andrea Dalla Torre, Paolo Gallo, Donatella Gubiani, Angelo Montanari, and Nicola Saccomanno. "Crowdsourced Reconstruction of Cellular Networks to Serve Outdoor Positioning: Modeling, Validation and Analysis." Sensors 23, no. 1 (2022): 352. http://dx.doi.org/10.3390/s23010352.

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Positioning via outdoor fingerprinting, which exploits the radio signals emitted by cellular towers, is fundamental in many applications. In most cases, the localization performance is affected by the availability of information about the emitters, such as their coverage. While several projects aim at collecting cellular network data via crowdsourcing observations, none focuses on information about the structure of the networks, which is paramount to correctly model their topology. The difficulty of such a modeling is exacerbated by the inherent differences among cellular technologies, the str

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Dahunsi, Folasade Mojisola, and Barry Dwolatzky. "Investigating Geometry-Aware Network-Based Positioning in Cellular Networks Using Neural Network Predictive Model." Wireless Personal Communications 90, no. 3 (2016): 1413–32. http://dx.doi.org/10.1007/s11277-016-3401-y.

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Zou, Dong Yao, Teng Fei Han, Dao Li Zheng, and He Lv. "Centroid Localization Algorithm Based on the Anchor Nodes Cellular Distribution." Applied Mechanics and Materials 475-476 (December 2013): 579–82. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.579.

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The node localization is one of the key technologies in wireless sensor networks. To the accurate positioning of the nodes as the premise and foundation, this paper presents a centroid localization algorithm based on Cellular network. First, the anchor nodes are distributed in a regular hexagonal cellular network. Unknown nodes collect the RSSI of the unknown nodes nearby, then select the anchor nodes whose RSSI is above the threshold. Finally, the average of these anchor nodes coordinates is the positioning results. MATLAB simulation results show that localization algorithm is simple and effe

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Wang, Junxiang, Canyang Guo, and Ling Wu. "Gated Recurrent Unit with RSSIs from Heterogeneous Network for Mobile Positioning." Mobile Information Systems 2021 (April 12, 2021): 1–7. http://dx.doi.org/10.1155/2021/6679398.

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Recently, research studies on Location-Based Services (LBSs) based on networks including cellular network and Wi-Fi network have gradually become popular. Received Signal Strength Indicators (RSSIs) from the network can be detected and collected by mobile devices to estimate the locations without adopting the Global Positioning System (GPS). Previous research studies utilized the RSSIs of only cellular network or only Wi-Fi network to estimate location, which leads to a two-fold predicament involving error limits of cellular network-based methods and environmental constraints of Wi-Fi network-

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Campos, Rafael Saraiva. "Evolution of Positioning Techniques in Cellular Networks, from 2G to 4G." Wireless Communications and Mobile Computing 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/2315036.

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This review paper presents within a common framework the mobile station positioning methods applied in 2G, 3G, and 4G cellular networks, as well as the structure of the related 3GPP technical specifications. The evolution path through the generations is explored in three steps at each level: first, the new network elements supporting localization features are introduced; then, the standard localization methods are described; finally, the protocols providing specific support to mobile station positioning are studied. To allow a better understanding, this paper also brings a brief review of the

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Jiménez-Martínez, María Jesús, Mónica Zabala Haro, Ángel Martín Furonés, and Ana Anquela Julián. "A GNSS–Cellular Network Hybridization Strategy for Robust Positioning." Applied Sciences 15, no. 11 (2025): 6300. https://doi.org/10.3390/app15116300.

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The hybridization of cellular networks and GNSS systems has gained increasing attention, especially in urban canyons and indoor environments where GNSS performance degrades significantly. Hybrid localization is part of the 3rd Generation Partnership Project (3GPP) standard, offering an effective solution when satellite visibility is limited. Additional cellular measurements can enhance the accuracy and reliability of standalone UE. Hybrid methods offer multiple benefits: an improved availability, continuity, and integrity; better signal penetration due to proximity; a lower power consumption;

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Campos, Rafael Saraiva, and Lisandro Lovisolo. "Genetic algorithm-based cellular network optimisation considering positioning applications." IET Communications 13, no. 7 (2019): 879–91. http://dx.doi.org/10.1049/iet-com.2018.5125.

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Abdulwahhab, Omar Waleed, and Sally Antoin Jergees. "Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems." Journal of Engineering 22, no. 1 (2016): 83–102. http://dx.doi.org/10.31026/j.eng.2016.01.06.

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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of

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Liu, Z., L. Chen, Z. Jiao, X. Lu, and Y. Ruan. "THE TOA ESTIMATION OF CELLULAR NETWORK SIGNALS BASED ON MACHINE LEARNING IN COMPLEX URBAN ENVIRONMENTS." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023 (December 5, 2023): 673–78. http://dx.doi.org/10.5194/isprs-annals-x-1-w1-2023-673-2023.

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Abstract. The precision location-based services in complex environment is a challenge in the field of navigation and positioning. With the continuous development of wireless communication technology in recent years, cellular network signals such as LTE and 5G have emerged as unique advantages in navigation and positioning applications. This paper presents a time-of-arrival (TOA) estimation method based on machine learning, which can use cellular network signals to obtain accurate ranging results in low signal-to-noise ratio conditions. For this purpose, we first present the cellular network si

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Gollapudi, Sreelakshmi, Lalit Pathak, Tushar Vrind, Diwakar Sharma, and Samir Mishra. "Indoor Positioning using cellular network and relay node for wearables." EAI Endorsed Transactions on Cloud Systems 4, no. 13 (2018): 156533. http://dx.doi.org/10.4108/eai.16-5-2018.156533.

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Bejarano-Luque, Juan Luis, Matías Toril, Mariano Fernández-Navarro, Luis Roberto Jiménez, and Salvador Luna-Ramírez. "Statistical Model for Mobile User Positioning Based on Social Information." Electronics 10, no. 15 (2021): 1782. http://dx.doi.org/10.3390/electronics10151782.

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In spite of the vast set of measurements provided by current mobile networks, cellular operators have problems pinpointing problematic locations because the origin of such measurements (i.e., user location) is usually not registered. At the same time, social networks generate a huge amount of data that can be used to infer population density. In this work, a data-driven model is proposed to deduce the statistical distribution of connections, exploiting the knowledge of network layout and population density in the scenario. Due to the absence of GPS measurements, the proposed method combines da

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Miao, Sheng, Liang Dong, and Jingyu Hou. "Dynamic base stations selection method for passive location based on GDOP." PLOS ONE 17, no. 12 (2022): e0272487. http://dx.doi.org/10.1371/journal.pone.0272487.

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For the problem of passive location in mobile cellular network, base stations (BSs) selection can improve positioning accuracy. Through the analysis of base station layout in cellular networks, using Geometric Dilution of Precision (GDOP) as the optimization objective, we propose a Dynamic Base Stations Selection (DBSS) method in a cellular unit. This method enables the system to dynamically select the positioning base station when positioning target in the detection area. DBSS mainly include three steps: nearest base station calculation, layout of base stations analysis, and base station sele

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Grujovic, Darko, and Mirjana Simic. "Adaptive algorithm for mobile user positioning based on environment estimation." Serbian Journal of Electrical Engineering 11, no. 3 (2014): 465–76. http://dx.doi.org/10.2298/sjee1403465g.

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This paper analyzes the challenges to realize an infrastructure independent and a low-cost positioning method in cellular networks based on RSS (Received Signal Strength) parameter, auxiliary timing parameter and environment estimation. The proposed algorithm has been evaluated using field measurements collected from GSM (Global System for Mobile Communications) network, but it is technology independent and can be applied in UMTS (Universal Mobile Telecommunication Systems) and LTE (Long-Term Evolution) networks, also.

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Tian, Xiaohua, Xinyu Wu, Hao Li, and Xinbing Wang. "RF Fingerprints Prediction for Cellular Network Positioning: A Subspace Identification Approach." IEEE Transactions on Mobile Computing 19, no. 2 (2020): 450–65. http://dx.doi.org/10.1109/tmc.2019.2893278.

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Hu, Zhengqun, Lirong Zhang, and Yuanfa Ji. "Applications of differential barometric altimeter in ground cellular communication positioning network." IET Science, Measurement & Technology 14, no. 3 (2020): 322–31. http://dx.doi.org/10.1049/iet-smt.2018.5316.

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18

Lind, Artjom, Shan Wu, and Amnir Hadachi. "Application of Gaussian Mixtures in a Multimodal Kalman Filter to Estimate the State of a Nonlinearly Moving System Using Sparse Inaccurate Measurements in a Cellular Radio Network." Sensors 23, no. 7 (2023): 3603. http://dx.doi.org/10.3390/s23073603.

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Kalman filter is a well-established accuracy correction method in control, guidance, and navigation. With the popularity of mobile communication and ICT, Kalman Filter has been used in many new applications related to positioning based on spatiotemporal data from the cellular network. Despite the low accuracy compared to Global Positioning System, the method is an excellent supplement to other positioning technologies. It is often used in sensor fusion setups as a complementary source. One of the reasons for the Kalman Filter’s inaccuracy lies in naive radio coverage approximation techniques b

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Mohammed, J. Alhasan, Muneer Abdulhussein Sarmad, and H. K. Khwayyir Ali. "Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 528–35. https://doi.org/10.11591/ijece.v11i1.pp528-535.

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The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. T

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Fokin, G. "EVOLUTION OF POSITIONING PROCEDURES IN MOBILE RADIO NETWORKS." Telecom IT 8, no. 1 (2020): 76–89. http://dx.doi.org/10.31854/2307-1303-2020-8-1-76-89.

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In this paper, we analyze the evolutionary features of positioning procedures in cellular 2G - 4G mobile radio systems. The analysis shows that along with the improvement of the architecture and methods of network positioning, new special mechanisms and procedures for the exchange of data appeared for the collection and processing of primary measurements during location estimation.

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21

Ahmad, Sabri, and Kosasih Rifki. "A network-based mobile positioning system using an optimization model." International Journal of Advances in Applied Sciences (IJAAS) 13, no. 2 (2024): 298–312. https://doi.org/10.11591/ijaas.v13.i2.pp298-312.

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The expansion of cellular network coverage facilitates the advancement of research on network-based positioning. We are interested in the signal fingerprinting method to predict the location of a mobile device. By this method, the device must be within the fingerprint coverage to have a successful location prediction. However, any disturbance in the signal propagation would decrease the prediction accuracy. We propose an optimization model based on generalized triangulation combined with a signal fingerprint which is treated more adaptively in responding to any signal disturbance. The triangul

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Alhasan, Mohammed J., Sarmad Muneer Abdulhussein, and Ali H. K. Khwayyir. "Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 528. http://dx.doi.org/10.11591/ijece.v11i1.pp528-535.

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The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. The eva

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Sabri, Ahmad, and Rifki Kosasih. "A network-based mobile positioning system using an optimization model." International Journal of Advances in Applied Sciences 13, no. 2 (2024): 298. http://dx.doi.org/10.11591/ijaas.v13.i2.pp298-312.

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The expansion of cellular network coverage facilitates the advancement of research on network-based positioning. We are interested in the signal fingerprinting method to predict the location of a mobile device. By this method, the device must be within the fingerprint coverage to have a successful location prediction. However, any disturbance in the signal propagation would decrease the prediction accuracy. We propose an optimization model based on generalized triangulation combined with a signal fingerprint which is treated more adaptively in responding to any signal disturbance. The triangul

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24

Wu, Ling, Chi-Hua Chen, and Qishan Zhang. "A Mobile Positioning Method Based on Deep Learning Techniques." Electronics 8, no. 1 (2019): 59. http://dx.doi.org/10.3390/electronics8010059.

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This study proposes a mobile positioning method that adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile stations. The recurrent neural networks with multiple consecutive timestamps can be applied to extract the features of time series data for the improvement of location estimation. In practical experimental environments, there are 4525 records, 59 different base stations, and 582 different Wi-Fi access points detected in Fuzhou University

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Gao, Yanbiao, Zhongliang Deng, Yuqi Huo, and Wenyan Chen. "Improving Non-Line-of-Sight Identification in Cellular Positioning Systems Using a Deep Autoencoding and Generative Adversarial Network Model." Sensors 24, no. 19 (2024): 6494. http://dx.doi.org/10.3390/s24196494.

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Positioning service is a critical technology that bridges the physical world with digital information, significantly enhancing efficiency and convenience in life and work. The evolution of 5G technology has proven that positioning services are integral components of current and future cellular networks. However, positioning accuracy is hindered by non-line-of-sight (NLoS) propagation, which severely affects the measurements of angles and delays. In this study, we introduced a deep autoencoding channel transform-generative adversarial network model that utilizes line-of-sight (LoS) samples as a

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Fokin, G. "Evolution of Positioning Radio Interfaces in Mobile Radio Networks." Telecom IT 8, no. 2 (2020): 77–91. http://dx.doi.org/10.31854/2307-1303-2020-8-2-77-91.

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In this paper, we analyze the evolutionary features of the radio interfaces of cellular 2G–4G mobile radio systems from the point of view of solving network positioning problems. The analysis shows that along with the improvement of the parameters of positioning signals, special mechanisms appeared for their formation, processing and reuse in different cells, which contributed to increasing the accuracy of the collection of primary measurements.

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Minetto, Alex, Fabio Dovis, Andrea Vesco, et al. "A Testbed for GNSS-Based Positioning and Navigation Technologies in Smart Cities: The HANSEL Project." Smart Cities 3, no. 4 (2020): 1219–41. http://dx.doi.org/10.3390/smartcities3040060.

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In urban contexts, the increasing density of electronic devices equipped with Global Navigation Satellite System (GNSS) receivers and complementary positioning technologies is attracting research and development efforts devoted to an improvement of the quality of life towards the smart city paradigm. Vehicular and pedestrian positioning and navigation capabilities are among the major drivers for innovation in this process. Ultra-low-cost electronics such as smartphones and Internet of Things (IoT) sensors aim at providing accurate and reliable positioning solutions through a set of promising s

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Álvarez-Merino, Carlos S., Hao Qiang Luo-Chen, Emil Jatib Khatib, and Raquel Barco. "WiFi FTM, UWB and Cellular-Based Radio Fusion for Indoor Positioning." Sensors 21, no. 21 (2021): 7020. http://dx.doi.org/10.3390/s21217020.

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High-precision indoor localisation is becoming a necessity with novel location-based services that are emerging around 5G. The deployment of high-precision indoor location technologies is usually costly due to the high density of reference points. In this work, we propose the opportunistic fusion of several different technologies, such as ultra-wide band (UWB) and WiFi fine-time measurement (FTM), in order to improve the performance of location. We also propose the use of fusion with cellular networks, such as LTE, to complement these technologies where the number of reference points is under-

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Starr, Daniel A. "A network of nuclear envelope proteins and cytoskeletal force generators mediates movements of and within nuclei throughout Caenorhabditis elegans development." Experimental Biology and Medicine 244, no. 15 (2019): 1323–32. http://dx.doi.org/10.1177/1535370219871965.

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Nuclear migration and anchorage, together referred to as nuclear positioning, are central to many cellular and developmental events. Nuclear positioning is mediated by a conserved network of nuclear envelope proteins that interacts with force generators in the cytoskeleton. At the heart of this network are linker of nucleoskeleton and cytoskeleton (LINC) complexes made of Sad1 and UNC-84 (SUN) proteins at the inner nuclear membrane and Klarsicht, ANC-1, and Syne homology (KASH) proteins in the outer nuclear membrane. LINC complexes span the nuclear envelope, maintain nuclear envelope architect

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Xu, Lei, Yu Feng Zhang, Jian Guo, and Lian Gao. "The Wireless Network Positioning Strategies Basing on Mobile Terminal." Advanced Materials Research 546-547 (July 2012): 1124–29. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1124.

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With the continuous development of terminal technologies, the use of mobile terminals is becoming more and more diverse. Many value-added services brought by such applications gradually become to be the firm's new profit opportunity. The location itself has great value; with the display of electronic map or with the support of geographic information database, a variety of information can be shown, tracked and handled. Such location-based services (LBS) is widely used in the field of public wireless data, and mobile location services is recognized as the most attractive wireless data value-adde

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Oliveira, Francisco, Miguel Luís, and Susana Sargento. "Machine Learning for the Dynamic Positioning of UAVs for Extended Connectivity." Sensors 21, no. 13 (2021): 4618. http://dx.doi.org/10.3390/s21134618.

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Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV posit

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Baena, Eduardo, Sergio Fortes, Francisco Muro, Carlos Baena, and Raquel Barco. "Beyond REM: A New Approach to the Use of Image Classifiers for the Management of 6G Networks." Sensors 23, no. 17 (2023): 7494. http://dx.doi.org/10.3390/s23177494.

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The management of cellular networks, particularly within the environment rapidly advancing to 6G, presents considerable challenges due to the highly dynamic radio environment. Traditional tools such as Radio Environment Maps (REMs) have proven inadequate for real-time network changes, underlining the need for more sophisticated solutions. In response to these challenges, this work introduces a novel approach that harnesses the unprecedented power of state-of-the-art image classifiers for network management. This method involves the generation of Network Synthetic Images (NSIs), which are enric

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Lai, Wei-Kuang, and Ting-Huan Kuo. "Vehicle Positioning and Speed Estimation Based on Cellular Network Signals for Urban Roads." ISPRS International Journal of Geo-Information 5, no. 10 (2016): 181. http://dx.doi.org/10.3390/ijgi5100181.

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Kurniawan, Oki. "PENGARUH BRAND POSITIONING DAN CONSUMPTION VALUE TERHADAP CONSUMER CHOICE BEHAVIOR (STUDI PADA PENGGUNA LAYANAN DATA XL)." Journal of Innovation in Business and Economics 7, no. 2 (2017): 87. http://dx.doi.org/10.22219/jibe.vol7.no2.87-94.

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Expansion of cellular network that provide faster data access makes rivalry between cellular operator switch from voice and sms to data service. This study has an objective to explore the influence of brand position to consumer choice behavior with consumption values as moderating variable based on Theory of Consumption Values in the context of XL data service. Brand positioning as a marketing stimuli has an important role as value creation that create a value to fill the consumer wants and needs. Hypothesis testing was performed with Structural Equation Model-Partial Least Square (SEM-PLS) on

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Fokin, G. A., and D. B. Volgushev. "Development of SDR-based Network Positioning Technology. LTE Reference Signals Reception and Processing Procedures." Herald of the Siberian State University of Telecommunications and Informatics 17, no. 1 (2023): 52–65. http://dx.doi.org/10.55648/1998-6920-2023-17-1-52-65.

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Introduction. The search for technical solutions to improve the positioning accuracy of devices using the infrastructure of base stations of existing and planned cellular radio networks is an important area of research and development in the last decade. Interest in network positioning is due to the unreliable reception of signals from global navigation satellite systems in dense urban areas. The instrument for experimental approbation of technical solutions is the software and hardware of the SDR software defined radio technology. This work is a continuation of the research on the use of SDR

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Zhou, Yiting, Tingfang Wu, Yelu Jiang, et al. "DeepNup: Prediction of Nucleosome Positioning from DNA Sequences Using Deep Neural Network." Genes 13, no. 11 (2022): 1983. http://dx.doi.org/10.3390/genes13111983.

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Nucleosome positioning is involved in diverse cellular biological processes by regulating the accessibility of DNA sequences to DNA-binding proteins and plays a vital role. Previous studies have manifested that the intrinsic preference of nucleosomes for DNA sequences may play a dominant role in nucleosome positioning. As a consequence, it is nontrivial to develop computational methods only based on DNA sequence information to accurately identify nucleosome positioning, and thus intend to verify the contribution of DNA sequences responsible for nucleosome positioning. In this work, we propose

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Mu, Qin, Muqing Wu, and Huixuan Zhou. "Generalization Investigation for Artificial Intelligence-Based Positioning in IIoT." Symmetry 15, no. 5 (2023): 992. http://dx.doi.org/10.3390/sym15050992.

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In recent years, IIoT scenarios show increasing demand for high-precision positioning. Cellular-based positioning plays a very important role in this application area. The cellular-based positioning system can be categorized as an asymmetric processing system. In this system, multiple base stations transmit positioning reference signaling to one device and the device derives its coordinates based on the measurement of the positioning reference signal by using certain positioning algorithms. The classical positioning algorithms encounter great challenges in satisfying the stringent precision re

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Fortes, Sergio, Carlos Baena, Javier Villegas, Eduardo Baena, Muhammad Zeeshan Asghar, and Raquel Barco. "Location-Awareness for Failure Management in Cellular Networks: An Integrated Approach." Sensors 21, no. 4 (2021): 1501. http://dx.doi.org/10.3390/s21041501.

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Recent years have seen the proliferation of different techniques for outdoor and, especially, indoor positioning. Still being a field in development, localization is expected to be fully pervasive in the next few years. Although the development of such techniques is driven by the commercialization of location-based services (e.g., navigation), its application to support cellular management is considered to be a key approach for improving its resilience and performance. When different approaches have been defined for integrating location information into the failure management activities, they

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Jean-François, D. Essiben1 Luc E. Ihonock1 and Yong S. Joe2. "ENHANCED PERFORMANCE BYHYPERBOLIC COMPENSATION TECHNIQUEIN CELLULAR WIRELESS NETWORKS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 8, no. 3 (2019): 126–32. https://doi.org/10.5281/zenodo.2607815.

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Being applicable for almost every scenario, a mobile localization of the cellular network has gained increasing interest in recent years. Since Received Signal Strength (RSS) information is available in all mobile phones, RSS-based techniques have become the preferred method for a localization of Global System for Mobile (GSM) communications. We use a COST 231-Hata propagation model with directional and omnidirectional antennas to determine a position of the target. To compare the performance of accurate mobile location, we consider both a classical hyperbolic technique, based on time differen

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Amponis, Georgios, Thomas Lagkas, Maria Zevgara, et al. "Drones in B5G/6G Networks as Flying Base Stations." Drones 6, no. 2 (2022): 39. http://dx.doi.org/10.3390/drones6020039.

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Advances in the fields of networking, broadband communications and demand for high-fidelity low-latency last-mile communications have rendered as-efficient-as-possible relaying methods more necessary than ever. This paper investigates the possibility of the utilization of cellular-enabled drones as aerial base stations in next-generation cellular networks. Flying ad hoc networks (FANETs) acting as clusters of deployable relays for the on-demand extension of broadband connectivity constitute a promising scenario in the domain of next-generation high-availability communications. Matters of mobil

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Ding, Zhenke, Zhongliang Deng, Enwen Hu, Bingxun Liu, Zhichao Zhang, and Mingyang Ma. "A New Scene Sensing Model Based on Multi-Source Data from Smartphones." Sensors 24, no. 20 (2024): 6669. http://dx.doi.org/10.3390/s24206669.

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Smartphones with integrated sensors play an important role in people’s lives, and in advanced multi-sensor fusion navigation systems, the use of individual sensor information is crucial. Because of the different environments, the weights of the sensors will be different, which will also affect the method and results of multi-source fusion positioning. Based on the multi-source data from smartphone sensors, this study explores five types of information—Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), cellular networks, optical sensors, and Wi-Fi sensors—characterizi

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Ma, Lin, Ningdi Jin, Yongliang Zhang, and Yubin Xu. "RSRP difference elimination and motion state classification for fingerprint-based cellular network positioning system." Telecommunication Systems 71, no. 2 (2018): 191–203. http://dx.doi.org/10.1007/s11235-018-0490-9.

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Chen, Bao Quan, Yong Yi Mao, Yang Yang, and Ping Xu. "Based on Wavelet Transform of TDOA/AOA Location Tracking Algorithm." Applied Mechanics and Materials 427-429 (September 2013): 1772–75. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1772.

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In cellular network mobile station location, the actual measured values non-line-of-sight error exists, makes the precision positioning algorithm based on the measured value is lower, aiming at the effects of non-line-of-sight error on the positioning performance, this paper proposes a new algorithm to reduce non line-of-sight error. Using wavelet transform to signal de-noising effect, eliminate the error in the measured value and reuse method of TDOA/AOA location algorithm to estimate mobile station location, with a certain distance threshold to mobile station location tracking. Simulation re

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Košuda, Marek. "Signals of Opportunity: Using Signal Defined Radio to Identify Potential Candidate." Repüléstudományi Közlemények 31, no. 2 (2019): 67–76. http://dx.doi.org/10.32560/rk.2019.2.5.

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This paper deals with the prospect of using cellular network signals as one of the candidates from the signals of opportunity as a supplementary or alternative source for navigation and positioning via onboard software defined radio. A low-cost system for modelling GSM coverage over a particular area is proposed.

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Hua, Huy Cuong, Grigoriy Fokin, and Ha Nam Nguyen. "Positioning of Devices in LTE Networks. Part 2. Analysis of Base Station Topology Impact on Coordinate Estimation Accuracy." Telecom IT 12, no. 3 (2024): 13–28. https://doi.org/10.31854/2307-1303-2024-12-3-13-28.

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Purpose. In recent decades, the development of positioning services in 4G LTE and 5G NR networks has been actively progressing, necessitating improvements in coordinate estimation accuracy. Earlier, the analysis conducted in the first part demonstrated that signal bandwidth significantly impacts positioning accuracy. This study investigates the influence of base station (BS) topology on coordinate estimation accuracy. The primary indicative factor of BS topology in space is the geometric dilution of precision (DOP) in positioning. The objective of this work is to analyze the influence of the B

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Chen, Chien-Sheng, Jium-Ming Lin, and Chin-Tan Lee. "Neural Network for WGDOP Approximation and Mobile Location." Mathematical Problems in Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/369694.

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This paper considers location methods that are applicable in global positioning systems (GPS), wireless sensor networks (WSN), and cellular communication systems. The approach is to employ the resilient backpropagation (Rprop), an artificial neural network learning algorithm, to compute weighted geometric dilution of precision (WGDOP), which represents the geometric effect on the relationship between measurement error and positioning error. The original four kinds of input-output mapping based on BPNN for GDOP calculation are extended to WGDOP based on Rprop. In addition, we propose two novel

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Liu, Xia, Baizheng Wang, and Wen Shao. "Research on the Application of Vehicle-Road Cooperative Autonomous Driving." Scientific Journal of Technology 6, no. 7 (2024): 55–63. http://dx.doi.org/10.54691/1zrvyj33.

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In order to solve the safety problem of bicycle intelligence under extreme conditions, a vehicle-road cooperative autonomous driving solution is proposed. The solution completes the real-time data interaction between intelligent networked vehicles and C-V2X (Cellular Vehicle-to-Everything) cloud platform through cellular network communication technology, GPS high-precision positioning technology, edge cloud collaboration and edge computing technologies, realizes "vehicle-road-cloud" digital information sharing, and improves vehicle driving safety and road traffic efficiency.

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Lin, Chun Hao, Yen Szu Liu, Chi Hua Chen, Bon Yeh Lin, and Chi Chun Lo. "A Real-Time Campus Guidance System Based on Energy Efficient Location Determination Method." Advanced Materials Research 211-212 (February 2011): 485–89. http://dx.doi.org/10.4028/www.scientific.net/amr.211-212.485.

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Recently guidancesystem is becoming more popular, as more people realize its benefits. There have been many developments on campus guidance system (CGS) in personal digital assistant (PDA) and smart phone. The building and promotion of the energy efficient location determination method is an important part of CGS. The cellular-based location determination using RSS from cellular network is more immediately, power-effective, and easy to deploy and maintain than traditional methods. In this paper, we design the CGS which provides the fingerprint position algorithm (FPA) using RSS from cellular n

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Fokin, G. A., and D. B. Volgushev. "Development of SDR-based network positioning technology. LTE reference signals reception and processing validation." Herald of the Siberian State University of Telecommunications and Information Science 17, no. 3 (2023): 23–33. http://dx.doi.org/10.55648/1998-6920-2023-17-3-23-33.

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Introduction. The positioning of devices according to the base stations reference signals of LTE cellular radio networks deployed everywhere is an important area of research and development that is in demand due to dense urban development with unreliable signal reception from global navigation satellite systems. The instrument for experimental approbation of technical solutions is the software and hardware of the SDR software defined radio technology. This work continues the study on the use of SDR technology for network positioning problems in terms of the experimental testing of the device f

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You, Yuan, and Chang Wu. "Indoor Positioning System With Cellular Network Assistance Based on Received Signal Strength Indication of Beacon." IEEE Access 8 (2020): 6691–703. http://dx.doi.org/10.1109/access.2019.2963099.

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