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Journal articles on the topic 'Predicted Received Signal Strength (RSS)'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Ayidu, Nneka Joy, and V. O. Elaigwu. "PATHLOSS PREDICTION MODEL IN WLAN PROPAGATION." FUDMA JOURNAL OF SCIENCES 7, no. 3 (2023): 1–5. http://dx.doi.org/10.33003/fjs-2023-0703-1822.

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Pathloss propagation in urban, suburban, and rural environments has a significant impact on wireless communication networks. Different propagation models have been developed for network locations. The different terrains are unique in their topological features and environmental factors. Therefore, a propagation model suitable for one terrain may not be suitable for another propagation environment for pathloss prediction. This paper proposes a signal prediction model with an 802.11 b/g wireless local area network (WLAN) infrastructure at 2.4 GHz. The models are backed by extensive received sign

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Subedi, Santosh, and Jae-Young Pyun. "Lightweight Workload Fingerprinting Localization Using Affinity Propagation Clustering and Gaussian Process Regression." Sensors 18, no. 12 (2018): 4267. http://dx.doi.org/10.3390/s18124267.

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Fingerprinting localization approach is widely used in indoor positioning applications owing to its high reliability. However, the learning procedure of radio signals in fingerprinting is time-consuming and labor-intensive. In this paper, an affinity propagation clustering (APC)-based fingerprinting localization system with Gaussian process regression (GPR) is presented for a practical positioning system with the reduced offline workload and low online computation cost. The proposed system collects sparse received signal strength (RSS) data from the deployed Bluetooth low energy beacons and tr

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Akinbolati, Akinsanmi, Yusuf Isiaq Omotosho, Idris Adamu, Muftahu Suleiman, and Sabiru Aminu Yaradua. "Pathloss Assessment of a Terrestrial Digital UHF Channel over Kano City, Nigeria." Nigerian Journal of Physics 33, S (2024): 15–22. http://dx.doi.org/10.62292/njp.v33(s).2024.228.

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Path loss assessment is an important factor in wireless communications to ensure quality of service. This study involves the measurement of Received Signal Strength (RSS) of Digital Terrestrial Television (DTTV) Star Times Station in Kano at 1 km intervals along three routes. Data were gathered during dry and wet season months in the year 2022. The path loss along the routes were computed based on the Okumura-Hata model. It was observed that path losses were higher during wet than dry season months. The result also indicates a higher negative correlation coefficient (R) of -0.745 between Line

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Akinbolati, Akinsanmi, Yusuf Isiaq Omotosho, Idris Adamu, Muftahu Suleiman, and Sabiru Aminu Yaradua. "Pathloss Assessment of a Terrestrial Digital UHF Channel over Kano City, Nigeria." Nigerian Journal of Physics 33, no. 2 (2024): 15–22. http://dx.doi.org/10.62292/njp.v33i2.2024.228.

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Path loss assessment is an important factor in wireless communications to ensure quality of service. This study involves the measurement of Received Signal Strength (RSS) of Digital Terrestrial Television (DTTV) Star Times Station in Kano at 1 km intervals along three routes. Data were gathered during dry and wet season months in the year 2022. The path loss along the routes were computed based on the Okumura-Hata model. It was observed that path losses were higher during wet than dry season months. The result also indicates a higher negative correlation coefficient (R) of -0.745 between Line

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Li, You, Zhouzheng Gao, Zhe He, et al. "Wireless Fingerprinting Uncertainty Prediction Based on Machine Learning." Sensors 19, no. 2 (2019): 324. http://dx.doi.org/10.3390/s19020324.

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Although wireless fingerprinting has been well researched and widely used for indoor localization, its performance is difficult to quantify. Therefore, when wireless fingerprinting solutions are used as location updates in multi-sensor integration, it is challenging to set their weight accurately. To alleviate this issue, this paper focuses on predicting wireless fingerprinting location uncertainty by given received signal strength (RSS) measurements through the use of machine learning (ML). Two ML methods are used, including an artificial neural network (ANN)-based approach and a Gaussian dis

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Sung, Kwangjae. "Pedestrian Positioning Using an Enhanced Ensemble Transform Kalman Filter." Sensors 23, no. 15 (2023): 6870. http://dx.doi.org/10.3390/s23156870.

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Due to the unavailability of GPS indoors, various indoor pedestrian positioning approaches have been designed to estimate the position of the user leveraging sensory data measured from inertial measurement units (IMUs) and wireless signal receivers, such as pedestrian dead reckoning (PDR) and received signal strength (RSS) fingerprinting. This study is similar to the previous study in that it estimates the user position by fusing noisy positional information obtained from the PDR and RSS fingerprinting using the Bayes filter in the indoor pedestrian positioning system. However, this study diff

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Mom, J. M., S. S. Tyokighir, and G. A. Igwue. "Evaluation of Some Path Reduction Factor Models Performance i n Tropical Location." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 3 (2021): 111–16. http://dx.doi.org/10.35940/ijrte.c6441.0910321.

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Performance evaluation of the ITU-R. P.530-17, Ghiani and Budalal model are considered for this work. It is found that the predicted values from the ITU-R and Ghiani distance factor models are seen to gradually decrease with an increase in path length for distances below 1km. Results further suggest that for a link length of 300 m, the Ghiani model predicts a 0.2499 dB (1.059 w) to 0.3273 dB (1.078 w) precipitation loss across all four (4) stations. For the ITU-R. P.530-17 model, a 3.4741 dB (2.225 w) to 5.329 dB (3.411 w) precipitation loss is estimated across all stations while the Budalal m

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Joseph, Mom, Tyokighir Soo, and Igwue Gabriel. "Evaluation of Some Path Reduction Factor Models Performance in Tropical Location." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 3 (2021): 111–16. https://doi.org/10.35940/ijrte.C6441.0910321.

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Performance evaluation of the ITU-R. P.530-17, Ghiani and Budalal model are considered for this work. It is found that the predicted values from the ITU-R and Ghiani distance factor models are seen to gradually decrease with an increase in path length for distances below 1km. Results further suggest that for a link length of 300 m, the Ghiani model predicts a 0.2499 dB (1.059 w) to 0.3273 dB (1.078 w) precipitation loss across all four (4) stations. For the ITU-R. P.530-17 model, a 3.4741 dB (2.225 w) to 5.329 dB (3.411 w) precipitation loss is estimated across all stations while the Budalal m

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Hua, Qiaozhi, Keping Yu, Zheng Wen, and Takuro Sato. "A Novel Base-Station Selection Strategy for Cellular Vehicle-to-Everything (C-V2X) Communications." Applied Sciences 9, no. 3 (2019): 556. http://dx.doi.org/10.3390/app9030556.

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Cellular vehicle-to-everything (C-V2X) communication facilitates the improved safety, comfort, and efficiency of vehicles and mobility by exchanging information between vehicles and other entities. In general, only the macrocell or only the femtocell is the communication infrastructure for C-V2X. Currently, a macro-femtocell network is used as the new C-V2X networking architecture. However, there are two unresolved problems for C-V2X in macro-femtocell networks. Firstly, vehicle mobility requires the frequent switching of connections between different base stations; invalid switching results i

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Mohammed, Alaelddin F. Y., Salman Md Sultan, Joohyung Lee, and Sunhwan Lim. "Deep-Reinforcement-Learning-Based IoT Sensor Data Cleaning Framework for Enhanced Data Analytics." Sensors 23, no. 4 (2023): 1791. http://dx.doi.org/10.3390/s23041791.

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The Internet of things (IoT) combines different sources of collected data which are processed and analyzed to support smart city applications. Machine learning and deep learning algorithms play a vital role in edge intelligence by minimizing the amount of irrelevant data collected from multiple sources to facilitate these smart city applications. However, the data collected by IoT sensors can often be noisy, redundant, and even empty, which can negatively impact the performance of these algorithms. To address this issue, it is essential to develop effective methods for detecting and eliminatin

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Jyoti, Madaan, and Indu Kashyap Dr. "A Novel Handoff Necessity Estimation Approach Based on Travelling Distance." International Journal of Advances in Applied Sciences (IJAAS) 7, no. 2 (2018): 105–16. https://doi.org/10.11591/ijaas.v7.i2.pp105-116.

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Mobility management is one of the most important challenges in Next Generation Wireless Networks (NGWNs) as it enables users to move across geographic boundaries of wireless networks. Nowadays, mobile communications have heterogeneous wireless networks offering variable coverage and Quality of Service (QoS). The availability of alternatives generates a problem of occurrence of unnecessary handoff that results in wastage of network resources. To avoid this, an efficient algorithm needs to be developed to minimize the unnecessary handoffs. Conventionally, whenever  Wireless Local Area Netwo

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Ahmadi, Hanen, and Ridha Bouallegue. "An accurate target tracking method in wireless sensor networks." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 3 (2022): 1589–98. https://doi.org/10.11591/ijeecs.v25.i3.pp1589-1598.

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Localization is a challenging research issue in various sectors of activity, particularly in dynamic indoor environment with high perturbation. Many existing localization techniques in wireless sensor networks are not efficient because of many constraints such as the high cost, the memory and energy limitation and the environmental noise effects. Thus, the development of novel methods of localization has become a great concern for the wireless sensor networks. In this paper, we propose a tracking method that combines regression tree and Kalman smoother filtering. Previously, regression tree ha

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Khandker, Syed, Joaquín Torres-Sospedra, and Tapani Ristaniemi. "Analysis of Received Signal Strength Quantization in Fingerprinting Localization." Sensors 20, no. 11 (2020): 3203. http://dx.doi.org/10.3390/s20113203.

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In recent times, Received Signal Strength (RSS)-based Wi-Fi fingerprinting localization has become one of the most promising techniques for indoor localization. The primary aim of RSS is to check the quality of the signal to determine the coverage and the quality of service. Therefore, fine-resolution RSS is needed, which is generally expressed by 1-dBm granularity. However, we found that, for fingerprinting localization, fine-granular RSS is unnecessary. A coarse-granular RSS can yield the same positioning accuracy. In this paper, we propose quantization for only the effective portion of the

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14

Abdel Meniem, Mohamed H., Ahmed M. Hamad, and Eman Shaaban. "GSM-Based Positioning Technique Using Relative Received Signal Strength." International Journal of Handheld Computing Research 4, no. 4 (2013): 38–51. http://dx.doi.org/10.4018/ijhcr.2013100103.

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Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. Database Correlation Method (DCM) is a positioning technology that based on a database of a premeasured location dependent variable such as Received Signal Strength (RSS). DCM has shown superior in terms of accuracy. Absolute RSS values received from a base station change with time, but the relative RSS (RRSS) values which refer to the relations of the RSS values between different base station

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Khoo, Hui Wen, Yin Hoe Ng, and Chee Keong Tan. "Optimized Received Signal Strength-Based Radio Map Interpolation for Indoor Positioning Systems." Journal of Cases on Information Technology 26, no. 1 (2024): 1–25. http://dx.doi.org/10.4018/jcit.355244.

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The most viable strategy to establish a dependable indoor positioning system is by employing the received signal strength (RSS) based fingerprinting technique, which encompasses both the offline and online phases. The offline phase involves constructing a radio map, which can be arduous in vast indoor environments. To tackle this, radio map interpolation is often used to interpolate RSS by utilizing the RSS recorded at a coarser level of known reference points (RPs). This paper proposes a novel RSS-based radio map interpolation to enhance the existing inverse distance weighting (IDW) interpola

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16

Zang, Yan Hong, Jin Song Wang, Lin Ling, and Pei Zhong Lu. "The Hybrid HMM for RSS-Based Localization in Wireless Sensor Networks." Applied Mechanics and Materials 347-350 (August 2013): 796–802. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.796.

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We proposea method of RSS-base localization in WSN (Wireless Sensor Network), called Hybrid HMM, to improve the stabilityof node localization basedon RSS(Received Signal Strength).This model utilizesHMM(Hidden Markov Model) to takeinto account the time factor when receiving the RSS sequence, andconverts the action of ranging into an operationof classification.For the received RSS used for localization,our Hybrid HMMwill compare it withthe preset RSS threshold value, and put the result into one of two categories for subsequent processing: If the received value is higher than the threshold value

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Raes, Willem, Nicolas Knudde, Jorik De Bruycker, Tom Dhaene, and Nobby Stevens. "Experimental Evaluation of Machine Learning Methods for Robust Received Signal Strength-Based Visible Light Positioning." Sensors 20, no. 21 (2020): 6109. http://dx.doi.org/10.3390/s20216109.

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In this work, the use of Machine Learning methods for robust Received Signal Strength (RSS)-based Visible Light Positioning (VLP) is experimentally evaluated. The performance of Multilayer Perceptron (MLP) models and Gaussian processes (GP) is investigated when using relative RSS input features. The experimental set-up for the RSS-based VLP technology uses light-emitting diodes (LEDs) transmitting intensity modulated light and a single photodiode (PD) as a receiver. The experiments focus on achieving robustness to cope with unknown received signal strength modifications over time. Therefore, s

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Xu, Yihuai, Xin Hu, Yimao Sun, et al. "High-Accuracy Height-Independent 3D VLP Based on Received Signal Strength Ratio." Sensors 22, no. 19 (2022): 7165. http://dx.doi.org/10.3390/s22197165.

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Visible light positioning (VLP) has attracted intensive attention from both academic and industrial communities thanks to its high accuracy, immunity to electromagnetic interference, and low deployment cost. In general, the receiver in a VLP system determines its own position by exploring the received signal strength (RSS) from the transmitter according to a pre-built RSS attenuation model. In such model-based methods, the LED’s emission power and the receiver’s height are usually required known and constant parameters to obtain reasonable positioning accuracy. However, the LED’s emission powe

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19

Perihanoglu, G. M., and H. Karaman. "SPATIAL PREDICTION OF RECEIVED SIGNAL STRENGTH FOR CELLULAR COMMUNICATION USING SUPPORT VECTOR MACHINE AND K-NEAREST NEIGHBOURS REGRESSION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W9-2024 (March 8, 2024): 291–97. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w9-2024-291-2024.

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Abstract. Signal strength maps are of great importance for cellular system providers in network planning and operation. Accurate prediction of signal strength is important for solving problems such as link quality. In this study, Received Signal Strength (RSS) prediction model is proposed for the 900 MHz band in the Van Yüzüncü Yıl University campus environment by using machine learning regression methods such as K- Nearest Neıghbours (KNN) and Support Vector Regression (SVR) together with Geographic Information Systems. For the training of this model, signal strength values taken from the RF

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Zhang, Chenbin, Ningning Qin, Yanbo Xue, and Le Yang. "Received Signal Strength-Based Indoor Localization Using Hierarchical Classification." Sensors 20, no. 4 (2020): 1067. http://dx.doi.org/10.3390/s20041067.

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Commercial interests in indoor localization have been increasing in the past decade. The success of many applications relies at least partially on indoor localization that is expected to provide reliable indoor position information. Wi-Fi received signal strength (RSS)-based indoor localization techniques have attracted extensive attentions because Wi-Fi access points (APs) are widely deployed and we can obtain the Wi-Fi RSS measurements without extra hardware cost. In this paper, we propose a hierarchical classification-based method as a new solution to the indoor localization problem. Within

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Yang, Fan, Jian Xiong, Jingbin Liu, et al. "A Pairwise SSD Fingerprinting Method of Smartphone Indoor Localization for Enhanced Usability." Remote Sensing 11, no. 5 (2019): 566. http://dx.doi.org/10.3390/rs11050566.

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Smartphone indoor localization has attracted considerable attention over the past decade because of the considerable business potential in terms of indoor navigation and location-based services. In particular, Wi-Fi RSS (received signal strength) fingerprinting for indoor localization has received significant attention in the industry, for its advantage of freely using off-the-shelf APs (access points). However, RSS measured by heterogeneous mobile devices is generally biased due to the variety of embedded hardware, leading to a systematical mismatch between online measures and the pre-establi

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Ahmad, Waqas, Ghassan Husnain, Sheeraz Ahmed, Farhan Aadil, and Sangsoon Lim. "Received Signal Strength-Based Localization for Vehicle Distance Estimation in Vehicular Ad Hoc Networks (VANETs)." Journal of Sensors 2023 (March 14, 2023): 1–15. http://dx.doi.org/10.1155/2023/7826992.

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Vehicular ad hoc networks (VANETs) are an eminent area of intelligent transportation systems (ITS) which includes vehicle tracking, positioning, and emergency warnings. For protective applications, vehicle localization in the urban area is a significant problem. Global Positioning Systems (GPS) are one of the many solutions that have been offered, although they do not offer accuracy. To locate a target vehicle accurately, a unique approach called received signal strength- (RSS-) based localization scheme has been proposed. By detecting signals within its range, it establishes communication thr

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Muttair, Karrar Shakir, Mahmood Farhan Mosleh, and Oras Ahmed Shareef. "Optimal transmitter location using multi-scale algorithm based on real measurement for outdoor communication." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (2022): 1384. http://dx.doi.org/10.11591/ijai.v11.i4.pp1384-1394.

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In the era of wireless network communication, the demand for determining the best transmitter (Tx) location is constantly increasing especially in outdoor environments and localization-based services. In this paper, localization optimal location of a Tx has been achieved in electrical engineering technical college by using received signal strength (RSS). We install practical devices in the college to measure the received signal strength in all the college regions. Where each device consists of two pieces which are the AirMAX sector directional antenna and signal broadcast piece (router board).

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Karrar, Shakir Muttair, Farhan Mosleh Mahmood, and Ahmed Shareef Oras. "Optimal transmitter location using multi-scale algorithm based on real measurement for outdoor communication." International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (2022): 1384–94. https://doi.org/10.11591/ijai.v11.i4.pp1384-1394.

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In the era of wireless network communication, the demand for determining the best transmitter (Tx) location is constantly increasing especially in outdoor environments and localization-based services. In this paper, localization optimal location of a Tx has been achieved in electrical engineering technical college by using received signal strength (RSS). We install practical devices in the college to measure the received signal strength in all the college regions. Where each device consists of two pieces which are the AirMAX sector directional antenna and signal broadcast piece (router board).

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Hong, Seok Mi. "A study of obstacles detection using RSS(Received Signal Strength)." Journal of Digital Policy and Management 11, no. 11 (2013): 321–26. http://dx.doi.org/10.14400/jdpm.2013.11.11.321.

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El Abkari, Safae, Jamal El Mhamdi, and El Hassan El Abkari. "Real-time RSS-based positioning system using neural network algorithm." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 3 (2021): 1601. http://dx.doi.org/10.11591/ijeecs.v22.i3.pp1601-1610.

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Locating services have come under the spotlight in recent years in various applications. However, locating methods that use received signal strength have low accuracy due to signal fluctuations. For this purpose, we present a Wi-Fi based locating system using artificial neural network to enhance the positioning process performances. We optimized the Levenberg Marquardt algorithm to propose the better configuration of the multi-layer time-delay perception neural network. We achieved an average error of 10.3 centimeters with a grid of 0.4 meter in four tests. Yet, due to the instability of the r

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Abkari, Safae El, Jamal El Mhamdi, and El Hassan El Abkari. "Real-time RSS-based positioning system using neural network algorithm." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 3 (2021): 1601–10. https://doi.org/10.11591/ijeecs.v22.i3.pp1601-1610.

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Locating services have come under the spotlight in recent years in various applications. However, locating methods that use received signal strength have low accuracy due to signal fluctuations. For this purpose, we present a Wi-Fi based locating system using artificial neural network to enhance the positioning process performances. We optimized the Levenberg Marquardt algorithm to propose the better configuration of the multi-layer time-delay perception neural network. We achieved an average error of 10.3 centimeters with a grid of 0.4 meter in four tests. Yet, due to the instability of the r

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28

Iman, Zubeiri, El Morabit Yasmina, and Mrabti Fatiha. "Genetic algorithm for vertical handover (GAfVH) in a heterogeneous networks." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 2534–40. https://doi.org/10.11591/ijece.v9i4.pp2534-2540.

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The fifth generation (5G) wireless system will deal with the growing demand of new multimedia and broadband application. The 5G network architecture is based on heterogeneous Radio Access Technologies (RATs). In such implementation the Vertical handover is a key issue. Up till now, systems are using simple mechanisms to make handover decision, based on the evaluation of the Received Signal Strength (RSS). In some cases these mechanisms are not efficient. This paper presents a new vertical handover algorithm based on Genetic Algorithm (GAfVH). It aims to reduce the number of unnecessary handove

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Ahmad, A., P. Claudio, A. Alizadeh Naeini, and G. Sohn. "WI-FI RSS FINGERPRINTING FOR INDOOR LOCALIZATION USING AUGMENTED REALITY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2020 (August 3, 2020): 57–64. http://dx.doi.org/10.5194/isprs-annals-v-4-2020-57-2020.

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Abstract. Indoor localization has attracted the attention of researchers for wide applications in areas like construction, facility management, industries, logistics, and health. The Received Signal Strength (RSS) based fingerprinting method is widely adopted because it has a lower cost over other methods. RSS is a measurement of the power present in the received radio signal. While this fingerprinting method is very popular, there is a significant amount of effort required for collecting fingerprints for indoor space. In this paper, we propose an RSS fingerprinting method using Augmented Real

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Barsocchi, Paolo, Stefano Chessa, Alessio Micheli, and Claudio Gallicchio. "Forecast-Driven Enhancement of Received Signal Strength (RSS)-Based Localization Systems." ISPRS International Journal of Geo-Information 2, no. 4 (2013): 978–95. http://dx.doi.org/10.3390/ijgi2040978.

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Khan, Faheem, Abdullah A. Al-Atawi, Abdullah Alomari, et al. "Development of a Model for Spoofing Attacks in Internet of Things." Mathematics 10, no. 19 (2022): 3686. http://dx.doi.org/10.3390/math10193686.

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Internet of Things (IoT) allows the integration of the physical world with network devices for proper privacy and security in a healthcare system. IoT in a healthcare system is vulnerable to spoofing attacks that can easily represent themselves as a legal entity of the network. It is a passive attack and can access the Medium Access Control address of some valid users in the network to continue malicious activities. In this paper, an algorithm is proposed for detecting spoofing attacks in IoT using Received Signal Strength (RSS) and Number of Connected Neighbors (NCN). Firstly, the spoofing at

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Akbar, Muhamad, Sholihin Sholihin, Suzan Zefi, and Muhammad Irfan Mishbahuddin Asyraf. "Rancang Bangun Aplikasi IPS Berdasarkan Fingerprinting Received Signal Stregth (RSS) Wifi dengan Algoritma K-Nearest Neighbor dan Auto Message Berbasis Android." Jurnal RESISTOR (Rekayasa Sistem Komputer) 6, no. 3 (2023): 145–55. http://dx.doi.org/10.31598/jurnalresistor.v6i3.1503.

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Indoor Positioning System (IPS) merupakan teknologi nirkabel yang digunakan untuk menemukan objek atau individu di dalam gedung menggunakan gelombang radio, medan magnet, sinyal akustik, atau sensor lain yang mampu mentransmisikan informasi melalui perangkat seluler. Sistem ini dapat menentukan posisi objek di dalam ruangan, termasuk orang, barang, dan lainnya. Algoritma K-Nearest Neighbor (KNN) memainkan peran kunci dalam alat Indoor Positioning System (IPS) berdasarkan Fingerprinting Received Signal Strength (RSS) WiFi. Tujuan utama algoritma KNN pada alat ini adalah untuk memastikan lokasi

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Kaur, Karamjeet, and Gianetan Singh Sekhon. "Security based on Received Signal Strength in Localization for Underwater Sensor Networks." Circulation in Computer Science 1, no. 2 (2016): 1–7. http://dx.doi.org/10.22632/ccs-2016-251-31.

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Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day’s large number of localization methods arrived for UWSNs. However, few of them take p

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Zubeiri, Iman, Yasmina El Morabit, and Fatiha Mrabti. "Genetic Algorithm for Vertical Handover (GAfVH)in a Heterogeneous networks." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 2534. http://dx.doi.org/10.11591/ijece.v9i4.pp2534-2540.

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<p>The fifth generation (5G) wireless system will deal with the growing demand of new multimedia and broadband application. The 5G network architecture is based on heterogeneous Radio Access Technologies (RATs). In such implementation the Vertical handover is a key issue. Up till now, systems are using simple mechanisms to make handover decision, based on the evaluation of the Received Signal Strength (RSS). In some cases these mechanisms are not Efficient.This paper presents a new vertical handover algorithm based on Genetic Algorithm (GAfVH). It aims to reduce the number of unnecessary

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As, Mansur, Hiroshi Shimizu, Brahim Benaissa, Kaori Yoshida, and Mario Köppen. "Calibration Cost Reduction of Indoor Localization Using Bluetooth Low Energy Beacon." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 1 (2022): 97–106. http://dx.doi.org/10.20965/jaciii.2022.p0097.

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Indoor localization based on Bluetooth low energy (BLE) beacons has been rapidly developed, and many approaches have been developed to achieve higher estimation accuracy. In these methods, the received signal strength (RSS) is the input. However, the measurement of indoor environments is affected easily; the signal may be reflected and attenuated by obstacles such as the human body, walls, and furniture, which creates a challenge for methods based on signal mapping. In this study, BLE signal characteristics are investigated in an indoor localization setting. An experiment is performed using on

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Waqas, Muhammad, Qamar Abbas, Ahsan Qureshi, et al. "Advanced Line-of-Sight (LOS) model for communicating devices in modern indoor environment." PLOS ONE 19, no. 7 (2024): e0305039. http://dx.doi.org/10.1371/journal.pone.0305039.

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The provision of Wireless Fidelity (Wi-Fi) service in an indoor environment is a crucial task and the decay in signal strength issues arises especially in indoor environments. The Line-of-Sight (LOS) is a path for signal propagation that commonly impedes innumerable indoor objects damage signals and also causes signal fading. In addition, the Signal decay (signal penetration), signal reflection, and long transmission distance between transceivers are the key concerns. The signals lose their power due to the existence of obstacles (path of signals) and hence destroy received signal strength (RS

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Yaro, Abdulmalik Shehu, Filip Maly, and Pavel Prazak. "A Survey of the Performance-Limiting Factors of a 2-Dimensional RSS Fingerprinting-Based Indoor Wireless Localization System." Sensors 23, no. 5 (2023): 2545. http://dx.doi.org/10.3390/s23052545.

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A receive signal strength (RSS) fingerprinting-based indoor wireless localization system (I-WLS) uses a localization machine learning (ML) algorithm to estimate the location of an indoor user using RSS measurements as the position-dependent signal parameter (PDSP). There are two stages in the system’s localization process: the offline phase and the online phase. The offline phase starts with the collection and generation of RSS measurement vectors from radio frequency (RF) signals received at fixed reference locations, followed by the construction of an RSS radio map. In the online phase, the

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Akinwole, Bukola H., and Abayomi I. O. Yussuff. "Investigating the Impacts of Tropospheric Parameters on Received Signal Strength of the Mobile Communication System." Annals of Science and Technology 8, no. 2 (2023): 63–73. http://dx.doi.org/10.2478/ast-2023-0016.

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Abstract Radio communication systems are crucial for information transmission, but they face challenges like interference and fading, which significantly impact network efficiency. Understanding propagation-related issues is crucial for optimizing networks. This study examined the influence of tropospheric parameters on the Received Signal Strength (RSS) of the Globacom communication system in Rivers State. Four tropospheric variables (air temperature, relative humidity, atmospheric pressure, and wind speed) are collected from the River State University of Science and Technology (RSUST) Enviro

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Khan, Umar F., Pavlos I. Lazaridis, Hamd Mohamed, et al. "An Efficient Algorithm for Partial Discharge Localization in High-Voltage Systems Using Received Signal Strength." Sensors 18, no. 11 (2018): 4000. http://dx.doi.org/10.3390/s18114000.

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The term partial discharge (PD) refers to a partial bridging of insulating material between electrodes that sustain an electric field in high-voltage (HV) systems. Long-term PD activity can lead to catastrophic failures of HV systems resulting in economic, energy and even human life losses. Such failures and losses can be avoided by continuously monitoring PD activity. Existing techniques used for PD localization including time of arrival (TOA) and time difference of arrival (TDOA), are complicated and expensive because they require time synchronization. In this paper, a novel received signal

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Chen, Yu-Chi, and Jyh-Ching Juang. "Outlier-Detection-Based Indoor Localization System for Wireless Sensor Networks." International Journal of Navigation and Observation 2012 (April 8, 2012): 1–11. http://dx.doi.org/10.1155/2012/961785.

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The paper exploits the outlier detection techniques for wireless-sensor-network- (WSN-) based localization problem and proposes an outlier detection scheme to cope with noisy sensor data. The cheap and widely available measurement technique—received signal strength (RSS)—is usually taken into account in the indoor localization system, but the RSS measurements are known to be sensitive to the change of the environment. The paper develops an outlier detection scheme to deal with abnormal RSS data so as to obtain more reliable measurements for localization. The effectiveness of the proposed appro

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Wu, Chunxiang, Yapeng Wang, Wei Ke, and Xu Yang. "A Dual-Branch Convolutional Neural Network-Based Bluetooth Low Energy Indoor Positioning Algorithm by Fusing Received Signal Strength with Angle of Arrival." Mathematics 12, no. 17 (2024): 2658. http://dx.doi.org/10.3390/math12172658.

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Indoor positioning is the key enabling technology for many location-aware applications. As GPS does not work indoors, various solutions are proposed for navigating devices. Among these solutions, Bluetooth low energy (BLE) technology has gained significant attention due to its affordability, low power consumption, and rapid data transmission capabilities, making it highly suitable for indoor positioning. Received signal strength (RSS)-based positioning has been studied intensively for a long time. However, the accuracy of RSS-based positioning can fluctuate due to signal attenuation and enviro

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Endurance Chukwuemeke Igbonoba, Ezekiel, and Adesola Temitope Bankole. "Investigative Assessment of the Impact of Perturbations on the Digital Terrestrial Television Broadcasting Signal." KIU Journal of Science, Engineering and Technology 2, no. 1 (2023): 75–83. http://dx.doi.org/10.59568/kjset-2023-2-1-10.

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This study examines the effects of perturbations on the digital terrestrial television broadcasting (DTTB) signal in Jos, Plateau State, Nigeria, using measurement-based performance analysis. In order to examine the effects of environmental perturbations on DTTB signal, measurement campaign used the Nigerian Television Authority, Integrated Television Services (ITS) digital video broadcasting -second generation (DVB-T2) signal. The aim of the research was to identify the environmental and atmospheric perturbations with highest impact on DTTB signal. Field measurement was accurately obtained th

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Ezhumalai, Balaji, Moonbae Song, and Kwangjin Park. "An Efficient Indoor Positioning Method Based on Wi-Fi RSS Fingerprint and Classification Algorithm." Sensors 21, no. 10 (2021): 3418. http://dx.doi.org/10.3390/s21103418.

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Wi-Fi received signal strength (RSS) fingerprint-based indoor positioning has been widely used because of its low cost and universality advantages. However, the Wi-Fi RSS is greatly affected by multipath interference in indoor environments, which can cause significant errors in RSS observations. Many methods have been proposed to overcome this issue, including the average method and the error handling method, but these existing methods do not consider the ever-changing dynamics of RSS in indoor environments. In addition, traditional RSS-based clustering algorithms have been proposed in the lit

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Imran, Sajida, and Young-Bae Ko. "A Novel Indoor Positioning System Using Kernel Local Discriminant Analysis in Internet-of-Things." Wireless Communications and Mobile Computing 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/2976751.

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WLAN based localization is a key technique of location-based services (LBS) indoors. However, the indoor environment is complex; received signal strength (RSS) is highly uncertain, multimodal, and nonlinear. The traditional location estimation methods fail to provide fair estimation accuracy under the said environment. We proposed a novel indoor positioning system that considers the nonlinear discriminative feature extraction of RSS using kernel local Fisher discriminant analysis (KLFDA). KLFDA extracts location features in a well-preserved kernelized space. In the new kernel featured space, n

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FASYA, ISTI, AKHMAD HAMBALI, and BRIAN PAMUKTI. "Penentuan Indoor Positioning System (IPS) menggunakan Metode Received Signal Strength (RSS) untuk Visible Light Communication (VLC)." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 11, no. 2 (2023): 325. http://dx.doi.org/10.26760/elkomika.v11i2.325.

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ABSTRAKPenentuan posisi di dalam ruangan merupakan hal yang penting untuk menjadikan petunjuk di dalam ruangan. Banyak metode lain yang sudah dilakukan penelitian tetapi ada beberapa kendala seperti tidak dapat digunakan di area sensitive dan biaya yang mahal. Pada penelitian ini kami mengusulkan untuk melakukan simulasi penentuan posisi menggunakan metode Received Signal Strength (RSS) dengan Light Emitting Diode (LED) dan Positive Intrinsic Negatif (PIN). Dengan asumsi pada ruangan tertutup yang berukuran 5 × 5 × 3 m3, kami melakukan simulasi 4 skenario posisi transmitter. Pada setiap skenar

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Veselý, Jiří, Petr Hubáček, and Jana Olivová. "The Power Gain Difference Method Analysis." Sensors 20, no. 11 (2020): 3018. http://dx.doi.org/10.3390/s20113018.

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In this paper, we propose a new approach to passively locate the 3D position of a signal source. This novel technique, called the power gain difference (PGD), is based only on measuring the received signal strength (RSS) with multiple sensors deployed in the area of interest, while the target transmit power or the equivalent isotropic radiated power (EIRP) is assumed to be unknown. Next, the signal source position is estimated using the knowledge of the ratios of RSS measured on different sensors. First, this article presents the geometric representation and the analytical solution of the mode

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Li, Suoping, Ke Wang, Jaafar Gaber, Sa Yang, and Wenwu Liang. "A Multifrequency Seamless Dual-Link Handover Scheme Based on Beamforming for High-Speed Railway." International Journal of Antennas and Propagation 2023 (March 29, 2023): 1–12. http://dx.doi.org/10.1155/2023/4879845.

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This paper proposes a multifrequency seamless dual-link handover scheme based on beamforming for the high-speed railway (HSR) communication, i.e., when the train travels to the edge of overlapping area of the adjacent two cells, a gain beam is assigned to the overlapping area by the target base station (BS) using a beamforming technique to cover the entire region to enhance the received signal strength (RSS) and handover opportunity. The switching antenna is allowed to handover multiple times to improve the traditional scheme and reduce the handover failure probability (HFP) greatly. In the pr

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Luckner, Marcin, and Rafał Górak. "Automatic Detection of Changes in Signal Strength Characteristics in a Wi-Fi Network for an Indoor Localisation System." Sensors 20, no. 7 (2020): 1828. http://dx.doi.org/10.3390/s20071828.

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This paper faces the issue of changing the received signal strength (RSS) from an observed access point (AP). Such a change can reduce the Quality of Service (QoS) of a Wi-Fi-based Indoor Localisation System. We have proposed a dynamic system based on an estimator of RSS using the readings from other APs. Using an optimal threshold, the algorithm recognises an AP that has changed its characteristics. Next, the system rebuilds the localisation model excluding the changed AP to keep QoS. For the tests, we simulated a change in the analysed Wi-Fi network by replacing the measured RSS by an RSS ob

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Akinbolati, Akinsanmi, and Moses Oludare Ajewole. "EFFECT OF SOME RADIO CLIMATIC FACTORS ON DIGITAL TERRESTRIAL TELEVISION SIGNAL IN A SAHEL SAVANNAH CITY OF NIGERIA." FUDMA JOURNAL OF SCIENCES 4, no. 2 (2020): 111–18. http://dx.doi.org/10.33003/fjs-2020-0402-150.

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This study investigates the effect of some radio climatic factors on the Received Signal Strength (RSS) of a Digital Terrestrial Television Broadcast Station (DTTBS) in Katsina City, Nigeria. The RSS was measured at intervals along selected routes around the station using a digital signal strength meter. GPS receiver was used to log the line of sight, geographic coordinates and heights of data points from the station. The atmospheric pressure, temperature and humidity corresponding to data points were concurrently measured using a compact weather station whereas the corresponding surface radio

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Zhimwang, J. Timothy, Opara C. Ezekwesili, and E. Pius Ogherohwo. "Empirical Estimation of Received Signal Strength, Multipath Fading, and Delay Spread in a 5G Urban Deployment in Nigeria." Nigerian Journal of Physics 34, no. 1 (2025): 166–71. https://doi.org/10.62292/10.62292/njp.v34i1.2025.391.

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As 5G networks are being deployed globally, it is critical to understand their radio propagation characteristics, particularly in complicated metropolitan contexts, in order to guarantee optimal network design and optimization. This study presents an empirical assessment of key performance indicators such as Received Signal Strength (RSS), multipath fading, and delay spread in a 5G urban deployment in Abuja, Nigeria. Using realistic propagation models and measurement scenarios in densely built-up areas, the study evaluates how urban morphology influences signal degradation and variability. Res

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