Low-Noise Amplifier Design for Improvement of Communication Range for Wake-up Receiver Based Wireless Sensor Network Application
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32807
Low-Noise Amplifier Design for Improvement of Communication Range for Wake-up Receiver Based Wireless Sensor Network Application

Authors: Ilef Ketata, Mohamed Khalil Baazaoui, Robert Fromm, Ahmad Fakhfakh, Faouzi Derbel

Abstract:

The integration of wireless communication, e.g. in realor quasi-real-time applications, is related to many challenges such as energy consumption, communication range, latency, quality of service, and reliability. The improvement of wireless sensor network performance starts by enhancing the capabilities of each sensor node. While consuming less energy, wake-up receiver (WuRx) nodes have an impact on reducing latency. The solution for sensitivity improvements of sensor nodes, and WuRx in particular, with an energy consumption expense is low-noise amplifier (LNAs) blocks placed in the RF Antenna. This paper presents a comparative study for improving communication range and decreasing the energy consumption of WuRx nodes.

Keywords: Wireless sensor network, wake-up receiver, duty-cycled, low-noise amplifier, envelope detector, range study.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 123

References:


[1] El Houssaini, D., Khriji, S., Besbes, K., and Kanoun, O. “Wireless sensor networks in agricultural applications”. In: Energy Harvesting for Wireless Sensor Networks. De Gruyter Oldenbourg, 2018, pp. 323–342.
[2] Bdiri, S., Derbel, F., and Kanoun, O. “A Tuned-RF Duty-Cycled Wake-Up Receiver with -90 dBm Sensitivity”. In: Sensors 18.1 (2018). ISSN: 1424-8220. DOI: 10.3390/s18010086. URL: https://www.mdpi.com/ 1424-8220/18/1/86.
[3] Fromm, R., Kanoun, O., and Derbel, F. “Reliable Wake-up Receiver with Increased Sensitivity using Low-Noise Amplifiers”. In: 2022 19th International Multi-Conference on Systems, Signals & Devices (SSD) (SSD’22). in press. S´etif, Algeria, May 2022.
[4] Amutha, J, Sharma, S., and Nagar, J. “WSN strategies based on sensors, deployment, sensing models, coverage and energy efficiency: Review, approaches and open issues”. In: Wireless Personal Communications 111.2 (2020), pp. 1089–1115.
[5] Guo, X., Zhao, C., Yang, X., and Sun, C. “A Deterministic Sensor Node Deployment Method with Target Coverage and Node Connectivity”. In: Artificial Intelligence and Computational Intelligence. Ed. by H. Deng, D. Miao, J. Lei, and F. L. Wang. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 201–207.
[6] Idrees, A. K. and Al-Yaseen, W. L. “Distributed genetic algorithm for lifetime coverage optimisation in wireless sensor networks”. In: Int. J. Adv. Intell. Paradigms 18.1 (2021), pp. 3–24. DOI: 10.1504/ IJAIP.2021. 112019. URL: https://doi.org/10.1504/IJAIP.2021.112019.
[7] Bdiri, S. and Derbel, F. “An Ultra-Low Power Wake-Up Receiver for Real-time constrained Wireless Sensor Networks”. In: May 2015. DOI: 10.5162/sensor2015/ D6.2.
[8] Pletcher, N. M., Gambini, S., and Rabaey, J. M. “A 2GHz 52 μW Wake-Up Receiver with -72dBm Sensitivity Using Uncertain-IF Architecture”. In: 2008 IEEE International Solid-State Circuits Conference - Digest of Technical Papers. 2008, pp. 524–633. DOI: 10.1109/ISSCC.2008.4523288.
[9] El Houssaini, D., Mohamed, Z., Khriji, S., Besbes, K., and Kanoun, O. “A filtered rssi model based on hardware characteristic for localization algorithm in wireless sensor networks”. In: 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA). IEEE Computer Society. 2018, pp. 118–123.
[10] Marques, J. P. P., Cunha, D. C., Harada, L. M., Silva, L. N., and Silva, I. D. “A cost-effective trilateration-based radio localization algorithm using machine learning and sequential least-square programming optimization”. In: Computer Communications 177 (2021), pp. 1–9. ISSN: 0140-3664. DOI: https://doi.org/10.1016/j.comcom.2021.06.005. URL: https://www.sciencedirect.com/science/article/pii/ S0140366421002292.
[11] Guidara, A., Derbel, F., Fersi, G., Bdiri, S., and Jemaa, M. B. “Energy-efficient on-demand indoor localization platform based on wireless sensor networks using low power wake up receiver”. In: Ad Hoc Networks 93 (2019), p. 101902.
[12] El Houssaini, D., Guesmi, A., Khriji, S., Keutel, T., Besbes, K., and Kanoun, O. “Experimental investigation on weather changes influences on wireless localization system”. In: 2019 IEEE International Symposium on Measurements & Networking (M&N). IEEE. 2019, pp. 1–6.
[13] Guidara, A., Fersi, G., Derbel, F., and Jemaa, M. B. “Impacts of Temperature and Humidity variations on RSSI in indoor Wireless Sensor Networks”. In: Procedia Computer Science 126 (2018), pp. 1072–1081.
[14] Guidara, A., Fersi, G., Jemaa, M. B., and Derbel, F. “A new deep learning-based distance and position estimation model for range-based indoor localization systems”. In: Ad Hoc Networks 114 (2021), p. 102445. ISSN: 1570-8705. DOI: https://doi.org/10.1016/j.adhoc. 2021 . 102445. URL: https : / /www. sciencedirect .com/ science/article/pii/S1570870521000214.
[15] Ketata, I., Fakhfakh, A., and Derbel, F. “Advanced evaluation platform-based RF attenuators for wireless sensor networks”. In: 2020 IEEE 6th World Forum on Internet of Things (WF-IoT). IEEE. 2020, pp. 1–6.
[16] Schott, L., Fromm, R., Bouattour, G., Kanoun, O., and Derbel, F. “Analytical and Experimental Performance Analysis of Enhanced Wake-Up Receivers Based on Low-Power Base-Band Amplifiers”. In: Sensors 22.6 (2022). ISSN: 1424-8220. DOI: 10 . 3390 / s22062169. URL: https://www.mdpi.com/1424-8220/22/6/2169.
[17] Imran, M., Said, A. M., and Hasbullah, H. “A survey of simulators, emulators and testbeds for wireless sensor networks”. In: 2010 International Symposium on Information Technology. Vol. 2. 2010, pp. 897–902. DOI: 10.1109/ITSIM.2010.5561571.