Method of Automatic Parameters Estimation of Radio Signals Generated According to LoRa Standard
Keywords:
method, radio signal, LoRa, linear frequency modulation, parameter, bandwidth, spreading factor, automationAbstract
Radio signals generated according to the LoRa standard (hereinafter referred to as LoRa radio signals) are widely used in telecommunication systems for both civil and military purposes, which is due primarily to their high immunity to interference.
The mathematical model of the LoRa radio signal is presented in the article. The relationship between radio signal modulation parameters, coding parameters, data transmission speed and interference immunity is shown. The characteristics of modern radio electronic components that support LoRa technology are analyzed, and the limits of modulation parameters ranges that can be used in a radio signal are determined. A method of automatic estimation of LoRa radio signal parameters is proposed, which consists of 4 stages. At the first stage, the carrier frequency and bandwidth are calculated by using characteristics of the signal amplitude-frequency spectrum. At the second stage, the information symbol duration is calculated by analyzing the features of the autocorrelation function. The obtained modulation parameters are rounded to the nearest constant values according to the minimum metric method. At the third stage, the spreading factor is calculated, which is analytically related to the bandwidth and the information symbol duration. At the fourth stage, the direction of the LoRa radio signal frequency change is determined. For this, two matched filters (for up-chirp and down-chirp symbols) are synthesized, the settings of which correspond to the LoRa radio signal parameters calculated in the previous three stages. The decision on the frequency change direction is made according to maximum signals amplitude at the output of the matched filters. The proposed method efficiency was verified by modeling in the MATLAB software and technical analysis of known LoRa data transmission protocols radio signals. It is shown that the method allows to correctly estimate the LoRa radio signals parameters with a probability close to 1 when the signal-to-noise ratio is greater than -5 dB.
References
References
LoRa technology. Applications. www.semtech.com.
Khutsoane O., Isong B. and Abu-Mahfouz A. M. (2017). IoT devices and applications based on LoRa/LoRaWAN. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, pp. 6107-6112, doi: 10.1109/IECON.2017.8217061.
Kamal M., Alam M., Sajak A. et al. (2023). Requirements, Deployments, and Challenges of LoRa Technology: A Survey. Computational Intelligence and Neuroscience, Article ID 5183062, 15 p. doi: 10.1155/2023/5183062.
I. de Almeida, M. Chafii, A. Nimr et al. (2021). Alternative Chirp Spread Spectrum Techniques for LPWANs. Electrical Engineering and Systems Science, 15 p. doi: 10.48550/arXiv.2102.09250.
Janssen T., BniLam N., Aernouts M., Berkvens R. et al. (2020). LoRa 2.4 GHz Communication Link and Range. Sensors, Vol. 20, Iss. 16, 4366; doi:10.3390/s20164366.
Falanji R., Heusse M., Duda A. (2022). Range and Capacity of LoRa 2.4 GHz. EAI Mobiquitous, 20 p, hal-03868942.
Gbadoubissa J., Ari A., Radoi E., Gueroui A. (2023). M-Ary Direct Modulation Chirp Spread Spectrum for Spectrally Efficient Communications. Information, Vol. 14, Iss. 6, 15 p. doi: 10.3390/info14060323.
Courjault J., Vrigneau B., Berder O. and Bhatnagar M. R. (2020). How robust is a LoRa communication against impulsive noise? IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, p. 1–6. doi: 10.1109/pimrc48278.2020.9217348.
Bor M., Roedig U. (2017). LoRa Transmission Parameter Selection. 13th International Conference on Distributed Computing in Sensor Systems, p. 27–34. doi: 10.1109/dcoss.2017.10.
Turčinović F., Vuković J., Božo S., and Šišul G. (2020). Analysis of LoRa Parameters in Real-World Communication. International Symposium ELMAR, P. 87–90. doi: 10.1109/elmar49956.2020.9219028.
Silva E., Figueiredo L., de Oliveira A., et al. (2023). Adaptive Parameters for LoRa-Based Networks Physical-Layer. Sensors, Vol. 23, Iss. 10, 4597; doi: 10.3390/s23104597.
Araujo D. C., Ferre G., Cavalcante C. C. and Guerreiro I. M. (2020). A Spectral Efficiency Enhancement for Chirp Spread Spectrum Downlink Communications. 2020 IEEE Latin-American Conference on Communications (LATINCOM), pp. 1-6, doi: 10.1109/LATINCOM50620.2020.9282266.
Yi Y., Zhao H., Wang Y. (2020). LoRa Signal Monitoring System of Multi-Node Software Define Radio. IEEE Wireless Communications and Networking Conference Workshops (WCNCW), pp. 1-5. doi: 10.1109/wcncw48565.2020.9124898.
Horne C., Peters N., Ritchie M. (2023). Classification of LoRa signals with real-time validation using the Xilinx Radio Frequency System-on-Chip. IEEE Access, Vol. 11, pp. 26211-26223. DOI: 10.1109/ACCESS.2023.3252170.
Ben G., Zheng X., Wang Y., et al. (2021). Local Search Maximum Likelihood Parameter Estimator of Chirp Signal. Applied Sciences, Vol. 11, Iss. 2, 673, DOI: 10.3390/app11020673.
E32-900T30D 868MHz/915MHz 30dBm new LoRa wireless module. User manual. Ver. 1.1. (2020). Chengdu Ebyte Electronic Technology Co., Ltd., 32 p.
SX1261/62. Datasheet. Rev 1.1. (2017). Semtech Corporation, 107 p.
SX1280/1281. Datasheet. Rev 3.2. (2020). Semtech Corporation, 158 p.
SX1272/73. Datasheet. Rev 4. (2019). Semtech Corporation, 129 p.
SX1276/77/78/79. Datasheet. Rev 5. (2016). Semtech Corporation, 129 p.
SX1276/SX1278 wireless modules E32 series. User manual. Ver. 1.3. (2018). Chengdu Ebyte Electronic Technology Co., Ltd., 30 p.
LLCC68. Datasheet. Rev 1.0. (2019). Semtech Corporation, 106 p.
E32-900T30D. SX1276 868MHz/915MHz DIP wireless module. User manual. Ver. 1.2. (2023). Chengdu Ebyte Electronic Technology Co., Ltd., 20 p.
E220-900T30D 868MHz/915MHz 30dBm LoRa wireless module. User manual. Ver. 1.0. (2020). Chengdu Ebyte Electronic Technology Co., Ltd., 22 p.
TBS CROSSFIRE R/C System. Adaptive Long Range Remote Control System. (2022). 88 p.
Kroese, D. P., Botev, Z., Taimre, T., & Vaisman, R. (2023). Data Science and Machine Learning: Mathematical and Statistical Methods, 513 p.
Benvenuto N., Cherubini G., Tomasin S. (2021). Algorithms for Communications Systems and their Applications, 2nd edition. Wiley, 960 p.
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