High Reliability in LoRaWAN

Coutaud, Ulysse; Heusse, Martin; Tourancheau, Bernard

doi:10.1109/pimrc48278.2020.9217220

Cited by 10 publications

(14 citation statements)

References 22 publications

(37 reference statements)

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“…In order to evaluate the performance of the considered RFTs in the presence of errors, two different error distributions are supported in Sim-RFT: a uniform error distribution [28]- [57], and a burst error distribution [34]- [50]. These error distributions cover a comprehensive set of characteristics of LoRaWAN networks such as frame loss over distance [31], [33], [34], [37], [41], [51]- [53], different uses cases [31], [35], [54]- [57], mobile or stationary devices [33], [46], [49], [50], network capacity [54], and collisions [33], [53]. Frame loss burstiness may be due to channel effects [34], [36], mobility [34], [35], limited coverage [38], [40], [41], [44], or opportunistic coverage [42]- [44].…”

Section: Error Patterns and Ratesmentioning

confidence: 99%

Evaluation of Receiver-Feedback Techniques for Fragmentation Over LPWANs

Aguilar

Vidal

Gómez

2022

IEEE Internet Things J.

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The Internet Engineering Task Force (IETF) has standardized a new framework for IPv6 support over Low Power Wide Area Networks (LPWANs), called Static Context Header Compression and Fragmentation (SCHC). SCHC includes acknowledgment (ACK)-based mechanisms for reliable fragmented packet transmission. For the latter, SCHC defines a Receiver-Feedback Technique (RFT), called Compressed Bitmap (CB), by which a receiver reports to the sender whether the fragments carrying a packet have been received or not. Such information is carried as ACK payload. Considering the extraordinary frame size and message rate constraints of LPWANs, ACK payload size becomes crucial. In this paper, we compare the performance of CB with that of several alternative RFTs, namely List of Lost Fragments (LLF), List of Deltas (LoD), and Uncompressed Bitmap (UB), where the latter is used as a benchmark. We evaluate the considered RFTs in terms of ACK size, number of Layer 2 (L2) frames needed to carry an ACK, and ACK Time on Air. Our analysis shows that the use of RFTs different from CB offers significant performance improvement in many scenarios. Furthermore, we provide guidance on which RFT should be used for different packet sizes, error rates and error patterns.

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Section: Error Patterns and Ratesmentioning

confidence: 99%

Evaluation of Receiver-Feedback Techniques for Fragmentation Over LPWANs

Aguilar

Vidal

Gómez

2022

IEEE Internet Things J.

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“…In a previous work [12], we improved the ADR protocol by relying on the characterization of the channel as a Rayleigh channel and the use of an application layer FEC algorithm. This solution is only tailored for a single cell LoRaWAN network, which is a major weakness for dense deployments composed of few to many gateways.…”

Section: Adaptive Data Ratementioning

confidence: 99%

“…The behavior of their experimental channel SNR distribution seems to follow a truncated exponential distribution which is expected from a censored Rayleigh channel. The LoRa channel characterization as Rayleigh is also supported by a different study in the same city [12]. LoRa can also be subject to periodic variation of the link quality: an experimental study exposes a periodic 20 dB fading over a 10 km LoRa transmissions that may be caused by daily variation of the air's refraction index combined to multi-path propagation [32].…”

Section: Lora/lorawan Link Characterizationmentioning

confidence: 99%

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LoRa Channel Characterization for Flexible and High Reliability Adaptive Data Rate in Multiple Gateways Networks

Coutaud¹,

Heusse²,

Tourancheau³

2021

Computers

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We characterize the LoRa channel in terms of multi-path fading, loss burstiness, and assess the benefits of Forward Error Correction as well as the influence of frame length. We make these observations by synthesizing extensive experimental measurements realized with The Things Network in a medium size city. We then propose to optimize the LoRaWAN Adaptive Data Rate algorithm based on this refined LoRa channel characterization and taking into account the LoRaWAN inherent macro-diversity from multi-gateway reception. Firstly, we propose ADRopt, which adjusts Spreading Factor and frame repetition number to maintain the communication below a target Packet Error Rate ceiling with optimized Time-On-Air. Secondly, we propose ADRIFECC, an extension of ADRopt in case an Inter-Frame Erasure Correction Code is available. The resulting protocol provides very high reliability even over low quality channels, with comparable Time on Air and similar downlink usage as the currently deployed mechanism. Simulations corroborate the analysis, both over a synthetic random wireless link and over replayed real-world packet transmission traces.

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“…• transmissions using CSS are robust with respect to interference and can survive overlapping transmissions leading to the capture effect [4], [5], [6], [7], [8]; • successful packet delivery also depends on channel conditions (e.g., Rayleigh fading [9], [10]) that may greatly influence the packet reception for transmissions over long distances (e.g., several kilometers in case of LoRa networks); • improving PDR when devices cannot rely on ACKs for retransmissions of lost packets requires some transmission redundancy in the form of inter-frame Error Correction Codes (ECC) or transmission repetitions [11], [10].…”

Section: Introductionmentioning

confidence: 99%

Frame Arrival Timing in LoRaWAN: Capacity Increase With Repeated Transmissions and More Channel Attenuation

Heusse

Caillouet

Duda

2022

2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

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This paper considers a LoRaWAN cell in which devices access the channel using the unslotted ALOHA protocol. We propose a model of this access method that combines the effects of collisions with channel fading, by which reception may get buried in noise. Unlike the existing models of LoRaWAN, our model takes into account the frame arrival timing: it distinguishes, on the one hand, the interference created by earlier transmissions with respect to the frame of interest, and on the other hand, the interference by the frames arriving later on.From the results of the model, we draw three observations regarding the improvement of Packet Delivery Ratio (PDR). First, it puts back under the spotlight the often overlooked fact that repeating frames is always beneficial when the desired PDR is above 60%, even though the extra packet transmissions create more collisions. Second, as soon as the node density becomes notable and collisions have a similar impact on losses as attenuation, adding a smaller spreading factor SF6 modulation into the cell list of transmission parameters allows increasing the coverage range. Third, the model shows that cell capacity sometimes grows with the distance to the gateway or with decreased node transmission power, a trend seldom observed in wireless networks.

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High Reliability in LoRaWAN

Cited by 10 publications

References 22 publications

Evaluation of Receiver-Feedback Techniques for Fragmentation Over LPWANs

Evaluation of Receiver-Feedback Techniques for Fragmentation Over LPWANs

LoRa Channel Characterization for Flexible and High Reliability Adaptive Data Rate in Multiple Gateways Networks

Frame Arrival Timing in LoRaWAN: Capacity Increase With Repeated Transmissions and More Channel Attenuation

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