THE EFFECT OF FOV ANGLE ON A RSSI-BASED VISIBLE LIGHT POSITIONING SYSTEM

THE EFFECT OF FOV ANGLE ON A RSSI-BASED VISIBLE LIGHT POSITIONING SYSTEM

The effect of field of view (FOV) angle on the positioning performance in a visible light positioning (VLP) system utilizing light-emitting diodes (LEDs) is examined. Due to its simplicity and low cost, the received signal strength indication (RSSI) technique with trilateration is used for distance measurement. Since being robust to noise sources, the optical code division multiple access (CDMA) is preferred for broadcasting the unique identification and location information of each LED at the same time. LEDs are deployed on the ceiling of a highly reflective room with the aim of providing homogenous and suitable lighting. The varying angle of FOV - 30 degrees up to 88 degrees with 2-degree increments - is considered in the photodetector (PD) to obtain the effect of FOV on six different VLP scenarios with respect to the number of LEDs. All scenarios have the non-line of sight (NLOS) channel models up to three reflections. Simulation results show that increasing the number of transmitters (Txs) decreases the distance error sensitivity to the changes in the FOV angle. Consequently, indoor scenarios with increased Txs allow the use of low FOV angles. Acceptable distance errors are obtained even in harsh conditions, i.e., near the corner of the room.

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  • Barry, J. R. (1994). Wireless Infrared Communications. New York: Springer.
  • Celik, Y., & Çolak, S. A. (2020). “Quadrature spatial modulation sub-carrier intensity modulation (QSM-SIM) for VLC”. Physical Communication, 38, 1-10.
  • Çelik, Y. (2019). “The effect of LED deployment on RSSI-based VLP systems”. European Journal of Science and Technology, 17, 823-832.
  • Do, T. H., & Yoo, M. (2016). “An in-depth survey of visible light communication based positioning systems”. Sensors, 16(5), 1–40.
  • Gfeller, F. R., & Bapst, U. (1979). “Wireless in-house data communication via diffuse infrared radiation”. Proceedings of the IEEE, 67(11), 1474–1486.
  • Gu, W., Aminikashani, M., Deng, P., & Kavehrad, M. (2016). “Impact of multipath reflections on the performance of indoor visible light positioning systems”. Journal of Lightwave Technology, 34(10), 2578–2587.
  • Gu W., Zhang, W., Kavehrad, M., & Feng, L. (2014). “Three-dimensional light positioning algorithm with filtering techniques for indoor environments”. Optical Engineering, 53(10), 107107-1–107107-11.
  • Guowei, Z., Zhan, X., & Dan, L. (2013). “Research and improvement on indoor localization based on RSSI fingerprint database and K-nearest neighbor points”. International Conference on Communications, Circuits and Systems (pp. 68-71). Chengdu, China.
  • Hann, S., Kim, J. H., Jung, S. Y., & Park, C. S. (2010). “White LED ceiling lights positioning systems for optical wireless indoor applications”. 36th European Conference and Exhibition on Optical Communication (pp. 1–3). Torino, Italy.
  • Hassan, N. U., Naeem, A., Pasha, M. A., Jadoon, T., & Yuen, C. (2015). “Indoor positioning using visible LED lights: A survey”. ACM Computing Surveys, 48(2), 1–32.
  • Hossain, A. K. M. M. & Soh, W. S. (2007). “A comprehensive study of Bluetooth signal parameters for localization”. 18th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (pp. 1–5). Athens, Greece.
  • Hui, L., Darabi, H., Banerjee, P., & Liu, J. (2007). “Survey of wireless indoor positioning techniques and systems”. IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews, 37(1), 1067–1080.
  • Kahn, J. M., Krause, W. J., & Carruthers, J. B. (1995). “Experimental characterization of non-directed indoor infrared channels”. IEEE Transactions on Communications, 43(2/3/4), 1613–1623.
  • Khan, L. U. (2017). “Visible light communication: Applications, architecture, standardization and research challenges”. Digital Communications and Networks, 3(2), 78–88.
  • Kim, H. S., Kim, D. R., Yang, S. H., Son, Y. H., & Han, S. K. (2013). “An indoor visible light communication positioning system using a RF carrier allocation technique”. Journal of Lightwave Technology, 31(1), 134–144.
  • Komine, T., Lee, J. H., Shinichiro, H., & Nakagawa, M. (2009). “Adaptive equalization system for visible light wireless communication utilizing multiple white LED lighting equipment”. IEEE Transactions on Wireless Communications, 8(6), 2892-2900.
  • Lausnay, S. D. Strycker, L. D., Goemaere, J. P., Stevens, N., & Nauwelaers, B. (2014). “Optical CDMA codes for an indoor localization system using VLC”. 3rd International Workshop in Optical Wireless Communications (pp. 1-5). Funchal, Madeira, Portugal.
  • Lausnay, S. D. Strycker, L. D., Goemaere, J. P., Stevens, N., & Nauwelaers, B. (2015). “Influence of MAI in a CDMA VLP system”. International Conference on Indoor Positioning and Indoor Navigation (pp. 1–9). Banff, AB, Canada.
  • Lee, K., Park, H., & Barry, J. R. (2011). “Indoor channel characteristics for visible light communications”. IEEE Communications Letters, 15(2), 217–219.
  • Li, L., Hu, P., Peng, C., Shen, G., & Zhao, F. (2014). “Epsilon: A visible light based positioning system”. 11th USENIX Symposium Networked Systems Design and Implementation (pp. 331–343). Seattle, WA, USA.
  • Lou, P., Zhang, H., Zhang, X., Yao, M., & Xu, Z. (2012). “Fundamental analysis for indoor visible light positioning system”, 1st International Workshop on Optical Wireless Communications (pp. 59–63). Bejing, China.
  • Mohammed, N. A., & Elkarim, M. A. (2015). “Exploring the effect of diffuse reflection on indoor localization systems based on RSSI-VLC”. Optics Express, 23(16), 20297–20313.
  • Mousa, F. I. K., Almaadeed, N., Busawon, K., Bouridane, A., Binns, R., Elliot, I. (2018). “Indoor visible light communication localization system utilizing received signal strength indication technique and trilateration method”. Optical Engineering, 57(1), 1–10.
  • Prince, G. B., & Little, T. D. C. (2012). “A two phase hybrid RSS/AoA algorithm for indoor device localization using visible light”. IEEE Global Communications Conference (pp. 3347-3352). Anaheim, CA, USA.
  • Qiu, Y., Chen, S., Chen, H. H., & Meng, W. (2018). “Visible light communications based on CDMA technology”. IEEE Wireless Communications, 25(2), 178–185.
  • Reichenbach F., Born, A., Timmermann, D., & Bill, R. (2006). “A distributed linear least squares method for precise localization with low complexity in wireless sensor networks”. 2nd IEEE International Conference on Distributed Computing in Sensor Systems (pp. 514-528). San Francisco, CA, USA.
  • Ruiz, A. R. J., Granja, F. S., Honorato, J. C. P., & Rosas, J. I. G. (2012). “Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements”. IEEE Transactions on Instrumentation and Measurement, 61(1), 178–189.
  • Seguel, F., Krommenacker, N., Charpentier, P., & Soto, I. (2019). “A novel range free visible light positioning algorithm for imaging receivers”.Optik, 195, 163028-1–163028-21.
  • Sendani, N., & Ghahramani, R. (2017). “Study the effect of FOV in Visible Light Communication”. International Research Journal of Engineering and Technology, 4(10), 759-763.
  • Sertthin, C., Tsuji, E., Nakagawa, M., Kuwano, S., & Watanabe, K. (2009). “A switching estimated receiver position scheme for visible light based indoor positioning system,” 4th International Symposium on Wireless Pervasive Computing (pp. 1–5). Melbourne, Australia.
  • Tang, W., Zhang, J., Chen, B., Liu, Y., Zuo, Y., Liu, S., Dai, Y. (2017). “Analysis of indoor VLC positioning system with multiple reflections”. 16th International Conference on Optical Communications and Networks (pp. 1–3). Wuzhen, China.
  • Xu, Y., Wang, Z., Liu, P., Chen, J., Han, S., … Yu, J., (2017). “Accuracy analysis and improvement of visible light positioning based on VLC system using orthogonal frequency division multiple access”. Optics Express, 25(26), 32618–32630.
  • Yang, S. H., Jeong, E. M., Kim, D. R., Kim, H. S., Son, Y. H., Han, S. K. (2013). “Indoor three-dimensional location estimation based on LED visible light communication”. Electronics Letters, 49(1), 1–2.
  • Yiu, S., Dashti, M., Claussen, H., & Perez-Cruz, F. (2016). “Locating user equipments and access points using RSSI fingerprints: A Gaussian process approach”. IEEE International Conference on Communications. (pp. 1-6). Kuala Lumpur, Malaysia.
  • Zekavat, S. A. R., & Buehrer, R. M. (2019). Handbook of Position Location: Theory, Practice, and Advances. Hoboken, NJ: John Wiley & Sons.
  • Zhang, W., Chowdhury, M. I. S., & Kavehrad, M. (2014). “Asynchronous indoor positioning system based on visible light communications”. Optical Engineering, 53(4), 045105-1–045105-10.
  • Zhang X., Duan, J., Fu, Y., & Shi, A. (2014). “Theoretical accuracy analysis of indoor visible light communication positioning system based on received signal strength indicator”. Journal of Light Wave Technology, 32(21), 4180–4186.
  • Zhou, Z., Kavehrad, M., & Deng, P. (2012). “Indoor positioning algorithm using light-emitting diode visible light communications”. Optical Engineering, 51(8), 085009-1–085009-6.
  • Zhuang, Y., Hua, L., Qi, L., Yang, J., Cao P., Cao Y., … Haas, H. (2018). “A survey of positioning systems using visible LED lights”. IEEE Communications Surveys & Tutorials, 20(3), 1963–1988.
  • Zhuang, Y., Syed, Z., Li, Y., & El-Sheimy, N. (2016). “Evaluation of two WiFi positioning systems based on autonomous crowdsourcing of handheld devices for indoor navigation”. IEEE Transactions on Mobile Computing, 15(8), 1982–1995.
  • Zhuang, Y., Yang, J., Li, Y., Qi, L., & El-Sheimy, N. (2016). “Smartphone-based indoor localization with Bluetooth low energy beacons”. Sensors, 16(5), 1-20.