Performance Comparison of TR and FSRUWB System Using Particle Filter: Effects of Frequency, Data Rate, Multi-Path and Multi-Channel Communication
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Abstract
In this study, we introduced a novel scheme based on Transmitted References (TR) and Frequency Shifted Reference (FSR) for ultra-wideband (UWB) system. By taking into account tracking loop-based particle filtering together with a data collecting approach for single and multi-path channel situations, the suggested method is an enhanced model. Each particle's location is determined using this filtering technique, which is then utilised to calculate the timing inaccuracy and regulate the UWB system's timing pulse. Also, it can tackle the multimodal distribution of errors then effectively approximate the optimal solution. The data distribution is discretised via a number of particles that are weighted samples evolving concerning time duration. The simulation results show that, in terms of error rate, number of particles, and delay response, the recommended model of FSR-UWB with particle filter performs better than the TR-UWB with and without considering particle filter.
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Darif, A., Saadane, R., & Aboutajdine, D. (2014). Performance Evaluation of WideMac Compared to ALOHA in term of Energy Consumption for IR-UWB based WSN. Journal of Emerging Technologies in Web Intelligence, 6(1). https://doi.org/10.4304/jetwi.6.1.54-58.
Zaki, A. I., Badran, E. F., & El-Khamy, S. E. (2016). Two Novel Space-Time Coding Techniques Designed for UWB MISO Systems Based on Wavelet Transform. PLOS ONE, 11(12),e0167990.https://doi.org/10.1371/journal.pone.0167990
Charlier, M., Quoitin, B., & Hauweele, D. (2019). Challenges in using time slotted channel hopping with ultra wideband communications. In Proceedings of the International Conference on Internet of Things Design and Implementation - IoTDI ’19 (pp. 82–93). New York, New York, USA: ACM Press. https://doi.org/10.1145/3302505.3310071
Banstola, R., Bera, R., & Bhaskar, D. (2013). Review and Design of UWB Transmitter and Receiver. International Journal of Computer Applications, 69(13), 25–28. https://doi.org/10.5120/11903-7978
Mohammed, M. S., Singh, M. J., & Abdullah, M. (2017). New TR-UWB Receiver Algorithm Design to Mitigate MUI in Concurrent Schemes. Wireless Personal Communications, 97(3), 4431–4450. https://doi.org/10.1007/s11277-017-4732-z
Umek, A., Tomaži?, S., & Kos, A. (2019). Application for Impact Position Evaluation in Tennis Using UWB Localization. Procedia Computer Science, 147, 307–313. https://doi.org/10.1016/j.procs.2019.01.269
Ray, K. P., & Thakur, S. S. (2019). Modified Trident UWB Printed Monopole Antenna. Wireless Personal Communications. https://doi.org/10.1007/s11277-019-06646-x
Torino, P. D. I. (2019). Repository ISTITUZIONALE A Useful Approximation to Add up Contributions in Ray Based EM Propagation Algorithms Session 3AP Poster Session 2, (September). Retrieved from https://iris.polito.it/retrieve/handle/11583/1958813/51313/3AP.pdf#page=16
Huo, Y., Dong, X., & Lu, P. (2017). Ultra-wideband transmitter design based on a new transmitted reference pulse cluster. ICT Express, 3(3), 142–147. https://doi.org/10.1016/j.icte.2017.07.001
Liang, Z., Zhang, G., Dong, X., & Huo, Y. (2018). Design and Analysis of Passband Transmitted Reference Pulse Cluster UWB Systems in the Presence of Phase Noise. IEEE Access, 6, 14954–14965. https://doi.org/10.1109/ACCESS.2018.2815708
Djapic, R., Leus, G., & van der Veen, A. (2005). Synchronization and Detection for Transmitted Reference UWB Systems. In Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. (pp. 1084–1088). IEEE. https://doi.org/10.1109/ACSSC.2005.1599926
Franz, S., & Mitra, U. (2006). Generalized UWB transmitted reference systems. IEEE Journal on Selected Areas in Communications, 24(4), 780–786. https://doi.org/10.1109/JSAC.2005.863829
Yi-Ling Chao, & Scholtz, R. A. (2004). Optimal and suboptimal receivers for ultra-wideband transmitted reference systems. In GLOBECOM ’03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489) (Vol. 2, pp. 759–763). IEEE. https://doi.org/10.1109/GLOCOM.2003.1258340
Gifford, W. M., & Win, M. Z. (2004). On transmitted-reference UWB communications. In Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. (Vol. 2, pp. 1526–1531). IEEE. https://doi.org/10.1109/ACSSC.2004.1399410
Sibbett, T., Moradi, H., & Farhang-Boroujeny, B. (2016). Novel Maximum-Based Timing Acquisition for Spread-Spectrum Communications. In 2016 IEEE Globecom Workshops (GC Wkshps) (pp. 1–7). IEEE. https://doi.org/10.1109/GLOCOMW.2016.7848972
Han, C., Akyildiz, I. F., & Gerstacker, W. H. (2017). Timing Acquisition and Error Analysis for Pulse-Based Terahertz Band Wireless Systems. IEEE Transactions on Vehicular Technology, 66(11), 10102–10113. https://doi.org/10.1109/TVT.2017.2750707
Liu, Y., Wu, Q., Zhang, Y., Gao, J., & Qiu, T. (2019). Cyclostationarity-based DOA estimation algorithms for coherent signals in impulsive noise environments. EURASIP Journal on Wireless Communications and Networking, 2019(1), 81. https://doi.org/10.1186/s13638-019-1410-8
Kroll, H., Korb, M., Weber, B., Willi, S., & Huang, Q. (2017). Maximum-Likelihood Detection for Energy-Efficient Timing Acquisition in NB-IoT. In 2017 IEEE Wireless Communications and Networking Conference Workshops (WCNCW) (pp. 1–5). IEEE. https://doi.org/10.1109/WCNCW.2017.7919084
Shen, X. (Sherman), Guizani, M., Caiming, R., Le-Ngoc, & Tho, Q. and. (2006). Ultra-Wideband Wireless Communications And Networks. Wireless Communications. Retrieved from http://read.pudn.com/downloads226/ebook/1061232/W C and Networks by MD/2072-0470011440.pdf
Huang, T.-J., & Yang, J.-F. (2017). An Effective Timing Synchronization Scheme for DHTR UWB Receivers. Wireless Personal Communications, 95(4), 3495–3508. https://doi.org/10.1007/s11277-017-4009-6
Yorio, Z. (2020). Improving a wireless localization system via machine learning techniques and security protocols. Retrieved from https://commons.lib.jmu.edu/cgi/viewcontent.cgi?article=1071&context=masters202029
Qiu, Y., Yang, Q., Deng, M., & Chen, K. (2020). Time synchronization and data transfer method for towed electromagnetic receiver. Review of Scientific Instruments, 91(9), 094501. https://doi.org/10.1063/5.0012218
Prager, S., Haynes, M. S., & Moghaddam, M. (2020). Wireless Subnanosecond RF Synchronization for Distributed Ultrawideband Software-Defined Radar Networks. IEEE Transactions on Microwave Theory and Techniques, 68(11), 4787–4804. https://doi.org/10.1109/TMTT.2020.3014876
Zhang, Z., Li, J., & Yang, X. (2020). Data Aggregation in Heterogeneous Wireless Sensor Networks by Using Local Tree Reconstruction Algorithm. Complexity, 2020, 1–14. https://doi.org/10.1155/2020/3594263
Goeckel, D. L., & Zhang, Q. (2007). Slightly Frequency-Shifted Reference Ultra-Wideband (UWB) Radio. IEEE Transactions on Communications, 55(3), 508–519. https://doi.org/10.1109/TCOMM.2007.892452
Zhang, Q., & Goeckel, D. L. (2007). Multiple-Access Slightly Frequency-Shifted Reference Ultra-Wideband Communications for Dense Multipath Channels. In 2007 IEEE International Conference on Communications (pp. 1083–1088). IEEE. https://doi.org/10.1109/ICC.2007.184
Zhang, J., Hu, H.-Y., Liu, L.-K., & Li, T.-F. (2007). Code-Orthogonalized Transmitted-Reference Ultra-Wideband (UWB) Wireless Communication System. In 2007 International Conference on Wireless Communications, Networking and Mobile Computing (pp. 528–532). IEEE. https://doi.org/10.1109/WICOM.2007.138
S. L. Bangare, “Classification of optimal brain tissue using dynamic region growing and fuzzy min-max neural network in brain magnetic resonance images”, Neuroscience Informatics, Volume 2, Issue 3, September 2022, 100019, ISSN 2772-5286, https://doi.org/10.1016/j.neuri.2021.100019.
S. L. Bangare, S. Prakash, K. Gulati, B. Veeru, G. Dhiman and S. Jaiswal, "The Architecture, Classification, and Unsolved Research Issues of Big Data extraction as well as decomposing the Internet of Vehicles (IoV)," 2021 6th International Conference on Signal Processing, Computing and Control (ISPCC), 2021, pp. 566-571, doi: 10.1109/ISPCC53510.2021.9609451.
S. L. Bangare, A. R. Khare, P. S. Bangare, “Code parser for object Oriented software Modularization”, International Journal of Engineering Science and Technology, ISSN: 0975-5462, Vol. 2 (12), 2010, 7262-7265..
Suneet Gupta, Sumit Kumar, Sunil L. Bangare, Shibili Nuhmani, Arnold C. Alguno, Issah Abubakari Samori, “Homogeneous Decision Community Extraction Based on End-User Mental Behavior on Social Media”, Computational Intelligence and Neuroscience, vol. 2022, Article ID 3490860, 9 pages, 2022. https://doi.org/10.1155/2022/3490860.
P. S. Bangare, P. N. Gandhi, S. L. Bangare, “The Campus Navigator: An Android Mobile Application”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 3, Issue 3, March 2014, Page(s) 5715-5717, ISSN (Online) : 2278.
Xu Wu, Dezhi Wei, Bharati P. Vasgi, Ahmed Kareem Oleiwi, Sunil L. Bangare, and Evans Asenso, “Research on Network Security Situational Awareness Based on Crawler Algorithm”, Security and Communication Networks, Hindawi, ISSN:1939-0114, E-ISSN:1939-0122, https://www.scopus.com/sourceid/18000156707.
Ajay S. Ladkat, Sunil L. Bangare, Vishal Jagota, Sumaya Sanober, Shehab Mohamed Beram, Kantilal Rane, Bhupesh Kumar Singh, "Deep Neural Network-Based Novel Mathematical Model for 3D Brain Tumor Segmentation", Computational Intelligence and Neuroscience, vol. 2022, Article ID 4271711, 8 pages, 2022. https://doi.org/10.1155/2022/4271711.
L.M.I. Leo Joseph, S.L. Bangare, et al., Methods to identify facial detection in deep learning through the use of real-time training datasets management, Efflatounia (ISSN 1110-8703) 5 (2) (2021) 1298–1311.