On the LoRa Modulation for IoT: Waveform Properties and Spectral Analysis
О модуляции LoRa для IoT: свойства формы сигнала и спектральный анализ
2019-05-27
SCID: 54.1/a6ewckb6
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Fresnel functionsLoRa modulationM-ary LoRacontinuous phase modulationcross-correlation of waveformsdiscrete and continuous spectrumspectral analysis
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Abstract (AI)
An important modulation technique for Internet of Things (IoT) is the one proposed by the low power long range (LoRa) alliance. In this paper, we analyze the M-ary LoRa modulation in the time and frequency domains. First, we provide the signal description in the time domain, and show that LoRa is a memoryless continuous phase modulation. The cross-correlation between the transmitted waveforms is determined, proving that LoRa can be considered approximately an orthogonal modulation only for large M. Then, we investigate the spectral characteristics of the signal modulated by random data, obtaining a closed-form expression of the spectrum in terms of Fresnel functions. Quite surprisingly, we found that LoRa has both continuous and discrete spectra, with the discrete spectrum containing exactly a fraction 1/M of the total signal power.
Key Findings
1
Closed-form expression for the spectrum with random data is derived in terms of Fresnel functions.
2
Cross-correlation analysis shows LoRa waveforms are approximately orthogonal only for large M.
3
LoRa M-ary modulation is a memoryless continuous phase modulation in the time domain.
4
LoRa signal has both continuous and discrete spectral components.
5
The discrete spectrum contains exactly a fraction 1/M of the total signal power.
Research Object
M-ary LoRa modulation waveform for IoT communications
Research Subject
Time- and frequency-domain properties including memoryless continuous-phase nature, cross-correlation/orthogonality for large M, and spectral characteristics (closed-form spectrum via Fresnel functions showing continuous and discrete components with discrete power fraction 1/M)
Publication Details
Publication Date
2019-05-27
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