Towards an SDR implementation of LoRa: Reverse-engineering, demodulation strategies and assessment over Rayleigh channel

Abstract

LoRa is a popular low-rate, Low-Power Wide Area Network (LPWAN) technology providing long range wireless access over unlicensed sub-GHz frequency bands to the Internet of Things (IoT). It has been used in many applications ranging from smart building to smart agriculture. LoRa is a patented modulation. However preliminary reverse-engineering efforts documented parts of it. In this article, we detail the different stages of LoRa transceivers: channel (de)coding, (de)whitening, (de)interleaving and (de)modulation with reverse-engineering in mind. Closed-form expressions for each of these stages are given, and different demodulation and decoding strategies are presented. This allows for a complete modelling of LoRa, which enables Software Defined Radio (SDR) implementations, as well as performance assessment under various channel conditions. These simulations show that LoRa systems have good properties for time and/or frequency selective channels (especially for the latter), thanks to the robustness of its underlying Chirp-Spread Spectrum (CSS) modulation.

Optimizing Power Allocation in LoRaWAN IoT Applications

“…As CSS and M-FSK belong to the same modulation family (orthogonal modulations), they perform exactly the same over AWGN channel [27]. Fig.…”

An Improved Demodulation for LoRa Through a Threshold-Based Detection of Error

“…It must be noted that the denominator is equal to 1 − P s|h as it corresponds to the probability that the non-central χ 2 variable is larger than all the other (centered) χ 2 variables. Let us then focus on the numerator of (24). For any k = 0, 1, .., N − 2, the cumulative distribution function (CDF) of the variable X = X k σ 2 is F X (x) = 1 − e −x , and the CDF of [28] for details).…”

“…Alternatively, the impact of the interference from other signals on the BER performance is investigated in [23]. Interestingly, some papers deal with the improvement of the LoRa demodulation through software define radio implementations [24] or cloud radio access network approach [25]. However, to the best of the author's knowledge, there is no dedicated paper dealing with signal processing algorithms for the improvement of the LoRa demodulation specifically (in term of error rate).…”

Theoretical Performance of LoRa System in Multipath and Interference Channels

“…The impact of M P C channels was investigated with the following studies. The authors in [16] evaluated the impact of time/frequency selective channels on demodulation process and highlighted the good LoRa resiliency on these channels and especially with the latter. Furthermore, an improved LoRa detector based on cyclic cross-correlation to combat M P C was also proposed in [17].…”

“…Proof. For a − = a (the previous symbol a − is equal to the current symbol a) and thanks to the property x a [−k] = x a [M − k], channel effect could be seen as a circular convolution and from (13) we obtain directly the DF T given in (16).…”