{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T14:59:36Z","timestamp":1772204376893,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic line of sight model with limited validity. The study considers the influence of noise as a performance indicator for the comparison between different design approaches. Three different ANN algorithms are considered, including Levenberg\u2013Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, to minimize the positioning error (\u03b5p) in the VLP system. The ANN design is optimized based on the number of neurons in the hidden layers, the number of training epochs, and the size of the training set. It is shown that, the ANN with Bayesian regularization outperforms the traditional received signal strength (RSS) technique using the non-linear least square estimation for all values of signal to noise ratio (SNR). Furthermore, in the inner region, which includes the area of the receiving plane within the transmitters, the positioning accuracy is improved by 43, 55, and 50% for the SNR of 10, 20, and 30 dB, respectively. In the outer region, which is the remaining area within the room, the positioning accuracy is improved by 57, 32, and 6% for the SNR of 10, 20, and 30 dB, respectively. Moreover, we also analyze the impact of different training dataset sizes in ANN, and we show that it is possible to achieve a minimum \u03b5p of 2 cm for 30 dB of SNR using a random selection scheme. Finally, it is observed that \u03b5p is low even for lower values of SNR, i.e., \u03b5p values are 2, 11, and 44 cm for the SNR of 30, 20, and 10 dB, respectively.<\/jats:p>","DOI":"10.3390\/s22082879","type":"journal-article","created":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T05:13:08Z","timestamp":1649481188000},"page":"2879","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["The Usage of ANN for Regression Analysis in Visible Light Positioning Systems"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6255-2749","authenticated-orcid":false,"given":"Neha","family":"Chaudhary","sequence":"first","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es and Departamento de Electr\u00f3nica, Telecomunica\u00e7\u00f5es e Inform\u00e1tica, Universidade de Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2015-1175","authenticated-orcid":false,"given":"Othman Isam","family":"Younus","sequence":"additional","affiliation":[{"name":"Optical Communications Research Group, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8071-9546","authenticated-orcid":false,"given":"Luis Nero","family":"Alves","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es and Departamento de Electr\u00f3nica, Telecomunica\u00e7\u00f5es e Inform\u00e1tica, Universidade de Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5780-9703","authenticated-orcid":false,"given":"Zabih","family":"Ghassemlooy","sequence":"additional","affiliation":[{"name":"Optical Communications Research Group, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7902-2143","authenticated-orcid":false,"given":"Stanislav","family":"Zvanovec","sequence":"additional","affiliation":[{"name":"Department of Electromagnetic Field, Faculty of Electrical Engineering, Czech Technical University in Prague, 16627 Prague, Czech Republic"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"key":"ref_1","unstructured":"Kaplan, E.D., and Hegarty, C.J. (1996). Understanding GPS: Principles and Applications, Artech House."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/JSEN.2015.2477444","article-title":"Tightly-Coupled Integration of WiFi and MEMS Sensors on Handheld Devices for Indoor Pedestrian Navigation","volume":"16","author":"Zhuang","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/MNET.2014.6963809","article-title":"Networking Solutions for Connecting Bluetooth Low Energy Enabled Machines to the Internet of Things","volume":"28","author":"Nieminen","year":"2014","journal-title":"IEEE Netw."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Priyantha, N.B., Miu, A.K.L., Balakrishnan, H., and Teller, S. (2001, January 16\u201321). The Cricket Compass for Context-Aware Mobile Applications. Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, Rome, Italy.","DOI":"10.1145\/381677.381679"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TSMCC.2007.905750","article-title":"Survey of Wireless Indoor Positioning Techniques and Systems","volume":"37","author":"Liu","year":"2007","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hsu, C.-W., Liu, S., Lu, F., Chow, C.-W., Yeh, C.-H., and Chang, G.-K. (2018, January 11\u201315). Accurate Indoor Visible Light Positioning System Utilizing Machine Learning Technique with Height Tolerance. Proceedings of the 2018 Optical Fiber Communications Conference and Exposition (OFC), San Diego, CA, USA.","DOI":"10.1364\/OFC.2018.M2K.2"},{"key":"ref_7","first-page":"1","article-title":"Indoor Positioning Using Visible LED Lights: A Survey","volume":"11","author":"Hassan","year":"2015","journal-title":"ACM Trans. Sens. Netw."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Do, T.-H., and Yoo, M. (2016). An In-Depth Survey of Visible Light Communication Based Positioning Systems. Sensors, 16.","DOI":"10.3390\/s16050678"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1109\/COMST.2016.2632427","article-title":"Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications","volume":"19","author":"Yassin","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2871","DOI":"10.1109\/COMST.2017.2743228","article-title":"Indoor Positioning Systems Based on Visible Light Communication: State of the Art","volume":"19","author":"Luo","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_11","first-page":"9","article-title":"Optical Wireless-Based Indoor Localization System Employing a Single-Channel Imaging Receiver","volume":"34","author":"Wang","year":"2016","journal-title":"J. Lightwave Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1109\/JLT.2012.2225826","article-title":"An Indoor Visible Light Communication Positioning System Using a RF Carrier Allocation Technique","volume":"31","author":"Kim","year":"2013","journal-title":"J. Lightwave Technol."},{"key":"ref_13","first-page":"4","article-title":"Indoor Three-Dimensional Positioning Based on Visible Light Communication Using Hamming Filter","volume":"2016","author":"Zheng","year":"2016","journal-title":"Opt. InfoBase Conf. Pap."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"120601","DOI":"10.3788\/COL201513.120601","article-title":"Combination of Light-Emitting Diode Positioning Identification and Time-Division Multiplexing Scheme for Indoor Location-Based Service","volume":"13","author":"Feng","year":"2015","journal-title":"Chin. Opt. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chaudhary, N., Alves, L.N., and Ghassemblooy, Z. (2019, January 27\u201328). Current Trends on Visible Light Positioning Techniques. Proceedings of the 2nd West Asian Colloquium on Optical Wireless Communications (WACOWC), Tehran, Iran.","DOI":"10.1109\/WACOWC.2019.8770211"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"05LT01","DOI":"10.1088\/2040-8986\/ab1389","article-title":"Efficient 3D Trilateration Algorithm for Visible Light Positioning","volume":"21","author":"Plets","year":"2019","journal-title":"J. Opt."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"050601","DOI":"10.3788\/COL201715.050601","article-title":"Artificial Neural-Network-Based Visible Light Positioning Algorithm with a Diffuse Optical Channel","volume":"15","author":"Guo","year":"2017","journal-title":"Chin. Opt. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2578","DOI":"10.1109\/JLT.2016.2541659","article-title":"Impact of Multipath Reflections on the Performance of Indoor Visible Light Positioning Systems","volume":"34","author":"Gu","year":"2016","journal-title":"J. Lightwave Technol."},{"key":"ref_19","first-page":"1","article-title":"Experimental Demonstration of an Indoor Positioning System Based on Artificial Neural Network","volume":"58","author":"Lin","year":"2019","journal-title":"Opt. Eng."},{"key":"ref_20","first-page":"1","article-title":"High-Precision Indoor Visible Light Positioning Using Deep Neural Network Based on the Bayesian Regularization with Sparse Training Point","volume":"11","author":"Zhang","year":"2019","journal-title":"IEEE Photonics J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"47769","DOI":"10.1109\/ACCESS.2019.2909761","article-title":"Robust 3D Indoor VLP System Based on ANN Using Hybrid RSS\/PDOA","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, W., and Kavehrad, M. (2012, January 9\u201311). A 2-D Indoor Localization System Based on Visible Light LED. Proceedings of the 2012 IEEE Photonics Society Summer Topical Meeting Series, Seattle, WA, USA.","DOI":"10.1109\/PHOSST.2012.6280711"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"085009","DOI":"10.1117\/1.OE.51.8.085009","article-title":"Indoor Positioning Algorithm Using Light-Emitting Diode Visible Light Communications","volume":"51","author":"Zhou","year":"2012","journal-title":"Opt. Eng"},{"key":"ref_24","unstructured":"Aminikashani, M., Gu, W., and Kavehrad, M. (2015). Indoor Location Estimation with Optical-Based OFDM Communications. arXiv."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chaudhary, N., Alves, L.N., and Ghassemlooy, Z. (2021). Impact of Transmitter Positioning and Orientation Uncertainty on RSS-Based Visible Light Positioning Accuracy. Sensors, 21.","DOI":"10.3390\/s21093044"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chaudhary, N., Younus, O.I., Alves, L.N., Ghassemlooy, Z., Zvanovec, S., and Le-Minh, H. (2021). An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy. Sensors, 21.","DOI":"10.3390\/s21030920"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TCE.2004.1277847","article-title":"Fundamental Analysis for Visible-Light Communication System Using LED Lights","volume":"50","author":"Komine","year":"2004","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"6519","DOI":"10.1007\/s11277-017-4853-4","article-title":"Localization in Wireless Sensor Networks Using Visible Light in Non-Line of Sight Conditions","volume":"97","author":"Pandey","year":"2017","journal-title":"Wirel. Pers. Commun."},{"key":"ref_29","unstructured":"Uysal, M., Baykas, T., and Jungnickel, V. (2018). IEEE 802.11bb Reference Channel Models for Indoor Environments, IEEE."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chaudhary, N., Alves, L.N., and Ghassemblooy, Z. (2019, January 27\u201328). Feasibility Study of Reverse Trilateration Strategy with a Single Tx for VLP. Proceedings of the 2nd West Asian Colloquium on Optical Wireless Communications (WACOWC), Tehran, Iran.","DOI":"10.1109\/WACOWC.2019.8770213"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ghassemlooy, Z., Popoola, W., and Rajbhandari, S. (2019). Optical Wireless Communications System and Channel Modelling with MATLAB\u00ae, CRC Press. [2nd ed.].","DOI":"10.1201\/9781315151724"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Shawky, S., El-Shimy, M.A., El-Sahn, Z.A., Rizk, M.R.M., and Aly, M.H. (2017, January 26\u201330). Improved VLC-Based Indoor Positioning System Using a Regression Approach with Conventional RSS Techniques. Proceedings of the 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017, Valencia, Spain.","DOI":"10.1109\/IWCMC.2017.7986406"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Chaudhary, N., Alves, L.N., and Ghassemlooy, Z. (2020, January 20\u201322). Impact of Transmitter Positioning Uncertainty on RSS-Based Visible Light Positioning Accuracy. Proceedings of the 12th IEEE\/IET International Symposium on Communication Systems, Networks and Digital Signal Processing-CSNDSP, Porto, Portugal.","DOI":"10.1109\/CSNDSP49049.2020.9249532"},{"key":"ref_34","unstructured":"Hagan, M.T., Demuth, H.B., and Beale, M. (1997). Neural Network Design, PWS Publishing Co."},{"key":"ref_35","unstructured":"Nwankpa, C., Ijomah, W., Gachagan, A., and Marshall, S. (2018). Activation Functions: Comparison of Trends in Practice and Research for Deep Learning. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1007\/BF02009686","article-title":"Computation of a Trust Region Step","volume":"7","author":"Shiquan","year":"1991","journal-title":"Acta Math. Appl. Sin."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1109\/TNN.2002.1031951","article-title":"Neighborhood Based Levenberg-Marquardt Algorithm for Neural Network Training","volume":"13","author":"Lera","year":"2002","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/S0893-6080(05)80056-5","article-title":"A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning","volume":"6","year":"1993","journal-title":"Neural Netw."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/8\/2879\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:50:49Z","timestamp":1760136649000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/8\/2879"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,8]]},"references-count":38,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22082879"],"URL":"https:\/\/doi.org\/10.3390\/s22082879","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,8]]}}}