期刊
IEEE INTERNET OF THINGS JOURNAL
卷 9, 期 20, 页码 19928-19944出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3173060
关键词
Modulation; Symbols; Bandwidth; Internet of Things; Time-domain analysis; Frequency shift keying; Chirp modulation; Chirp modulation; long range (LoRa); orthogonality conditions
资金
- EPSRC Grant Science of Sensor Systems (S4) programme [EP/N007565/1]
- Singapore Ministry of National Development
- National Research Foundation, Prime Minister's Office under the Land and Liveability National Innovation Challenge (L2NIC) Research Programme (L2 NIC) [L2NICTDF1-2017-3]
In this article, the authors provide a comprehensive understanding of long-range (LoRa) waveform theory and quantify its orthogonality for the first time. They present LoRa waveform expressions in continuous- and discrete-time domains and analyze the orthogonality measures between different LoRa spreading factors (SFs) through cross-correlation functions. The results show that LoRa modulation is nonorthogonal, with a maximum cross-correlation of less than 26% between different SFs, and this value decreases as the difference between SFs increases. The authors also highlight the impact of different bandwidths and temporal displacement on the cross-correlation.
In this article, we provide, for the first time, a comprehensive understanding of long-range (LoRa) waveform theory in order to quantify its orthogonality. We present LoRa waveform expressions in continuous- and discrete-time domains, and analyze measures of orthogonality between different LoRa spreading factors (SFs) through cross-correlation functions. The cross-correlation functions are analytically expressed in a general form and they account for diverse configuration parameters (bandwidth, SF, etc.) and different cases of signal displacements (time delay shift, frequency shift, etc.). We quantify their mean and maximum in all time domains. We highlight the impact of the temporal displacement and different bandwidths. The general result is that LoRa modulation is nonorthogonal. First, we observe that for same bandwidths, the largest maximum cross-correlation happens for same SF and is equal to 100% due to same symbols; whereas for different bandwidths, the largest maximum cross-correlation is no longer observed at the same SF. Second, the maximum cross-correlation is less than 26% between different SFs, is higher for closer SFs, and decreases as the difference between SFs increases. After downchirping, the maximum cross-correlation increases and the mean decreases compared to those before downchirping. Moreover, the maximum cross-correlation is insignificantly impacted by the temporal delay, which makes it valid to adopt for the performance analysis of both synchronous and asynchronous systems. Finally, we analyze by simulating the bit error probability statistics for different bandwidth ratios and highlighting their correlated behavior with the insights obtained from the maximum cross-correlation expressions.
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