LABeL

Kotsiou, Vasileios; Papadopoulos, Georgios Z.; Théoleyre, Fabrice

doi:10.1145/3127540.3127541

Cited by 29 publications

(3 citation statements)

References 24 publications

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“…For example, devices who approach full saturation could be assigned less and less time slots in the slotframe scheme as they approach their point of saturation. This would force the device to [58][59][60] blacklist undesirable channels based on interference. Such techniques could be adapted to blacklist channels for devices who are saturated in certain regulatory frequency bands.…”

Section: The Use Of Multiple Frequency Bands As a Mitigation Techniquementioning

confidence: 99%

Impact of EU duty cycle and transmission power limitations for sub-GHz LPWAN SRDs: an overview and future challenges

Saelens

Hoebeke

Shahid

et al. 2019

J Wireless Com Network

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Long-range sub-GHz technologies such as LoRaWAN, SigFox, IEEE 802.15.4, and DASH7 are increasingly popular for academic research and daily life applications. However, especially in the European Union (EU), the use of their corresponding frequency bands are tightly regulated, since they must confirm to the short-range device (SRD) regulations. Regulations and standards for SRDs exist on various levels, from global to national, but are often a source of confusion. Not only are multiple institutes responsible for drafting legislation and regulations, depending on the type of document can these rules be informational or mandatory. Regulations also vary from region to region; for example, regulations in the United States of America (USA) rely on electrical field strength and harmonic strength, while EU regulations are based on duty cycle and maximum transmission power. A common misconception is the presence of a common 1% duty cycle, while in fact the duty cycle is frequency band-specific and can be loosened under certain circumstances. This paper clarifies the various regulations for the European region, the parties involved in drafting and enforcing regulation, and the impact on recent technologies such as SigFox, LoRaWAN, and DASH7. Furthermore, an overview is given of potential mitigation approaches to cope with the duty cycle constraints, as well as future research directions. more and more relevant. For example, LoRa duty cycle limitations already impacts, among others, the throughput of the downlink communication, the (un)availability of acknowledgements, the feasibility of over the air firmware upgrades, geolocation inaccuracies, and scalability [1][2][3][4]. Several models predict that the probability of duty cycle violations during downlink communication will further increase, up to 20% for SigFox and 15% for LoRaWAN [5]. Similar impacts are expected for other technologies operating in sub-GHz radio frequency bands.However, despite the large impact of these regulations, many researchers are unaware of the exact limits and are not aware of mitigation techniques they can apply. Various institutes have each implemented regulations on the availability of radio spectrum for SRDs and their usage restrictions. This fragmentation causes confusion and misconceptions for researchers and manufacturers alike.

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Section: The Use Of Multiple Frequency Bands As a Mitigation Techniquementioning

confidence: 99%

Impact of EU duty cycle and transmission power limitations for sub-GHz LPWAN SRDs: an overview and future challenges

Saelens

Hoebeke

Shahid

et al. 2019

J Wireless Com Network

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“…If the future quality of a wireless link could be predicted in advance with a certain accuracy, e.g., in terms of frame delivery ratio (FDR), the communication protocol could exploit this information for trying to meet the specific requirements of industrial applications. For instance, when the quality of a specific channel is expected to worsen, the application can switch to another channel (suffering from less disturbance) to preserve communication reliability [14] or to prevent energy consumption from increasing [15]. As an alternative, it can change some network/communication parameters or diminish the amount of best-effort traffic (shaping) to privilege timesensitive data exchanges.…”

Section: Introductionmentioning

confidence: 99%

Linear Combination of Exponential Moving Averages for Wireless Channel Prediction

Formis,

Scanzio,

Cena

et al. 2023

2023 IEEE 21st International Conference on Industrial Informatics (INDIN)

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The ability to predict the behavior of a wireless channel in terms of the frame delivery ratio is quite valuable, and permits, e.g., to optimize the operating parameters of a wireless network at runtime, or to proactively react to the degradation of the channel quality, in order to meet the stringent requirements about dependability and end-to-end latency that typically characterize industrial applications.In this work, prediction models based on the exponential moving average (EMA) are investigated in depth, which are proven to outperform other simple statistical methods and whose performance is nearly as good as artificial neural networks, but with dramatically lower computational requirements. Regarding the innovation and motivation of this work, a new model that we called EMA linear combination (ELC), is introduced, explained, and evaluated experimentally. Its prediction accuracy, tested on some databases acquired from a real setup based on Wi-Fi devices, showed that ELC brings tangible improvements over EMA in any experimental conditions, the only drawback being a slight increase in computational complexity.

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“…In the first approach, all the nodes have the same list of channels, but this solution may become suboptimal, since the channels may present different quality for different network links, even if the nodes are close to each other [6]. In the second method, each pair of nodes can use different sets of channels [9], i.e. a specific blacklist is defined per link.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Channels Blacklists in TSCH Networks with Star and Tree Topologies

Queiroz

Gomes

Benavente-Peces

et al. 2018

Proceedings of the 14th ACM International Symposium on QoS and Security for Wireless and Mobile Networks

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The Time-Slotted Channel Hopping (TSCH) mode, defined by the IEEE 802.15.4e protocol, aims to reduce the effects of narrowband interference and multipath fading on some channels through the frequency hopping method. To work satisfactorily, this method must be based on the evaluation of the channel quality through which the packets will be transmitted to avoid packet losses. In addition to the estimation, it is necessary to manage channel blacklists, which prevents the sensors from hopping to bad quality channels. The blacklists can be applied locally or globally, and this paper evaluates the use of a local blacklist through simulation of a TSCH network in a simulated harsh industrial environment. This work evaluates two approaches, and both use a developed protocol based on TSCH, called Adaptive Blacklist TSCH (AB-TSCH), that considers beacon packets and includes a link quality estimation with blacklists. The first approach uses the protocol to compare a simple version of TSCH to configurations with different sizes of blacklists in star topology. In this approach, it is possible to analyze the channel adaption method that occurs when the blacklist has 15 channels. The second approach uses the protocol to evaluate blacklists in tree topology, and discusses the inherent problems of this topology. The results show that, when the estimation is performed continuously, a larger blacklist leads to an increase of performance in star topology. In tree topology, due to the simultaneous transmissions among some nodes, the use of smaller blacklist showed better performance.

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LABeL

Cited by 29 publications

References 24 publications

Impact of EU duty cycle and transmission power limitations for sub-GHz LPWAN SRDs: an overview and future challenges

Impact of EU duty cycle and transmission power limitations for sub-GHz LPWAN SRDs: an overview and future challenges

Linear Combination of Exponential Moving Averages for Wireless Channel Prediction

Evaluation of Channels Blacklists in TSCH Networks with Star and Tree Topologies

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