254 research outputs found

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

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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

    Analysis of Bidirectional ADR-Enabled Class B LoRaWAN Networks in Industrial Scenarios

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    [EN] Low-power wide-area network (LPWAN) technologies are becoming a widespread solution for wireless deployments in many applications, such as smart cities or Industry 4.0. However, there are still challenges to be addressed, such as energy consumption and robustness. To characterize and optimize these types of networks, the authors have developed an optimized use of the adaptative data rate (ADR) mechanism for uplink, proposed its use also for downlink based on the simulator ns-3, and then defined an industrial scenario to test and validate the proposed solution in terms of packet loss and energy.The research leading to these results received funding from the Horizon 2020 Programme of the European Commission under Grant Agreement No. 825631 "Zero Defect Manufacturing Platform (ZDMP)". It was also partially supported by the MCyU (Spanish Ministry of Science and Universities) under the project ATLAS (PGC2018-094151-B-I00).Todoli Ferrandis, D.; Silvestre-Blanes, J.; Sempere Paya, VM.; Planes, A. (2020). Analysis of Bidirectional ADR-Enabled Class B LoRaWAN Networks in Industrial Scenarios. Applied Sciences. 10(22):1-17. https://doi.org/10.3390/app10227964S1171022Ayoub, W., Samhat, A. E., Nouvel, F., Mroue, M., & Prevotet, J.-C. (2019). Internet of Mobile Things: Overview of LoRaWAN, DASH7, and NB-IoT in LPWANs Standards and Supported Mobility. IEEE Communications Surveys & Tutorials, 21(2), 1561-1581. doi:10.1109/comst.2018.2877382Zero Defect Manufacturing Platformhttps://www.zdmp.eu/Finnegan, J., Brown, S., & Farrell, R. (2018). Evaluating the Scalability of LoRaWAN Gateways for Class B Communication in ns-3. 2018 IEEE Conference on Standards for Communications and Networking (CSCN). doi:10.1109/cscn.2018.8581759Luvisotto, M., Tramarin, F., Vangelista, L., & Vitturi, S. (2018). On the Use of LoRaWAN for Indoor Industrial IoT Applications. Wireless Communications and Mobile Computing, 2018, 1-11. doi:10.1155/2018/3982646Kim, S., & Yoo, Y. (2018). Contention-Aware Adaptive Data Rate for Throughput Optimization in LoRaWAN. Sensors, 18(6), 1716. doi:10.3390/s18061716Ta, D.-T., Khawam, K., Lahoud, S., Adjih, C., & Martin, S. (2019). LoRa-MAB: A Flexible Simulator for Decentralized Learning Resource Allocation in IoT Networks. 2019 12th IFIP Wireless and Mobile Networking Conference (WMNC). doi:10.23919/wmnc.2019.8881393Abdelfadeel, K. Q., Cionca, V., & Pesch, D. (2018). Fair Adaptive Data Rate Allocation and Power Control in LoRaWAN. 2018 IEEE 19th International Symposium on ยซA World of Wireless, Mobile and Multimedia Networksยป (WoWMoM). doi:10.1109/wowmom.2018.8449737ns-3 Model Library, Online Resourcehttps://www.nsnam.org/doxygen/classns-3_1_1_hybrid_buildings_propagation_loss_model.html#detailsCode Repositoryhttps://github.com/dtodoli/ns3_lorawan_wor

    A fair channel hopping scheme for LoRa Networks with multiple single-channel gateways

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    LoRa is one of the most prominent LPWAN technologies due to its suitable characteristics for supporting large-scale IoT networks, as it offers long-range communications at low power consumption. The latter is granted mainly because end-nodes transmit directly to the gateways and no energy is spent in multi-hop transmissions. LoRaWAN gateways can successfully receive simultaneous transmissions on multiple channels. However, such gateways can be costly when compared to simpler single-channel LoRa transceivers, and at the same time they are configured to operate with pure-ALOHA, the well-known and fragile channel access scheme used in LoRaWAN. This work presents a fair, control-based channel hopping-based medium access scheme for LoRa networks with multiple single-channel gateways. Compared with the pure-ALOHA used in LoRaWAN, the protocol proposed here achieves higher goodput and fairness levels because each device can choose its most appropriate channel to transmit at a higher rate and spending less energy. Several simulation results considering different network densities and different numbers of single-channel LoRa gateways show that our proposal is able to achieve a packet delivery ratio (PDR) of around 18% for a network size of 2000 end-nodes and one gateway, and a PDR of almost 50% when four LoRa gateways are considered, compared to 2% and 6%, respectively, achieved by the pure-ALOHA approachinfo:eu-repo/semantics/publishedVersio

    LoRa ๋„คํŠธ์›Œํฌ์—์„œ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ์œ„ํ•œ ๋…ธ๋“œ ๊ธฐ๋ฐ˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2020. 8. ๊น€์ข…๊ถŒ.Recently, as Internet of Things (IoT) systems have increased and Wireless Sensor Network (WSN) has been expanding, studies related to them are increasing. Among them, the interest in long range communication technologies has increased. In this regard, Low Power Wide Area (LPWA) network technologies such as Long Range (LoRa), Weightless, and Sigfox have emerged. Also, various studies related to LoRa and LoRaWAN, which are available in Industrial Scientific and Medical (ISM) bands, are being conducted. In LoRa networks, the nodes are connected to the gateway by one hop to form a start topology. LoRa nodes use the transmission parameters such as Spreading Factor (SF), Transmission Power (TP), Bandwidth (BW), Coding Rate (CR), and Carrier Frequency (CF) to transmit frames. In this process, the frame losses and the collisions between frames may occur because of the channel condition and transmission timing. To alleviate this problem, LoRaWAN utilizes the ADR mechanism to select appropriate transmission parameters considering the channel condition on the node side. In addition, there is the ADR mechanism for allocating the transmission parameters on the server side. The ADR mechanisms maintain the connection between the server and the nodes, and set appropriate transmission parameters. However, these existing ADR mechanisms have some limitations. First, the server side ADR mechanism increases the overhead of the server in proportion to the transmitted frames. Second, it is difficult to quickly and efficiently respond to dynamic channel. Third, the transmission parameters selected by these ADR mechanisms may not be the optimal transmission parameters for energy efficiency. These problems cause large energy consumption of the battery-powered nodes and decrease performance when the channel condition changes dynamically. In this paper, we propose a Node-based ADR Mechanism (NbADR), which is the ADR mechanism for Class A nodes in confirmed mode to minimize the server load and maximize energy efficiency. The proposed mechanism responds quickly to the channel condition based on the downlink pattern and selects the transmission parameters for efficient energy consumption by utilizing Efficiency of Energy (EoE) metric. We analyze the efficiency of the transmission parameters selected through EoE, and conduct extensive experiments. In conclusion, NbADR is more effective in terms of energy efficiency than the existing ADR mechanisms. Additionally, NbADR guarantees throughput of LoRa networks even in dynamically changing channel environments and improves fairness between the nodes.์ตœ๊ทผ IoT ์‹œ์Šคํ…œ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ๋ฌด์„  ์„ผ์„œ ๋„คํŠธ์›Œํฌ๊ฐ€ ๋„“์–ด์ง€๋ฉด์„œ ์ด์™€ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ ์ค‘์—์„œ๋„ ์žฅ๊ฑฐ๋ฆฌ ํ†ต์‹  ๊ธฐ์ˆ ์— ๋Œ€ํ•œ ๊ด€์‹ฌ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ด์™€ ๊ด€๋ จํ•˜์—ฌ LoRa, Weightless, Sigfox์™€ ๊ฐ™์€ LPWA๋„คํŠธ์›Œํฌ ๊ธฐ์ˆ ๋“ค์ด ๋“ฑ์žฅํ•˜๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ISM ๋ฐด๋“œ์—์„œ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ LoRa์™€ LoRaWAN ๊ด€๋ จ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. LoRa ๋„คํŠธ์›Œํฌ์—์„œ ๋…ธ๋“œ๋“ค์€ ์Šคํƒ€ ํ† ํด๋กœ์ง€๋ฅผ ๊ตฌ์„ฑํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฒŒ์ดํŠธ์›จ์ด์™€ 1ํ™‰์œผ๋กœ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๋‹ค. LoRa ๋…ธ๋“œ๋“ค์€ ํ”„๋ ˆ์ž„์„ ์ „์†กํ•˜๊ธฐ ์œ„ํ•˜์—ฌ SF, TP, BW, CR, CF์™€ ๊ฐ™์€ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ๋‹ค. ์ด ๊ณผ์ •์—์„œ ์ฑ„๋„ ์ƒํƒœ์™€ ์ „์†ก ํƒ€์ด๋ฐ์œผ๋กœ ์ธํ•œ ํ”„๋ ˆ์ž„ ์†์‹ค๊ณผ ํ”„๋ ˆ์ž„ ๊ฐ„ ์ถฉ๋Œ์ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ์™„ํ™”ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ LoRaWAN์—์„œ๋Š” ๋…ธ๋“œ ์ธก์—์„œ ๋„คํŠธ์›Œํฌ ์ƒํ™ฉ์„ ๊ณ ๋ คํ•˜์—ฌ ์ ์ ˆํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ ํƒํ•˜๊ธฐ ์œ„ํ•œ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์‚ฌ์šฉํ•œ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€ ์„œ๋ฒ„ ์ธก์—์„œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ํ• ๋‹นํ•˜๋Š” ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ์กด์žฌํ•œ๋‹ค. ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค์€ ์„œ๋ฒ„์™€ ๋…ธ๋“œ์˜ ์—ฐ๊ฒฐ์„ ์œ ์ง€ํ•˜๊ณ  ์ ์ ˆํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ค์ •ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ๊ธฐ์กด์˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค์€ ์ผ๋ถ€ ํ•œ๊ณ„์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ, ์„œ๋ฒ„ ์ธก ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ์ „์†กํ•˜๋Š” ํ”„๋ ˆ์ž„์— ๋น„๋ก€ํ•˜์—ฌ ์„œ๋ฒ„์˜ ๋ถ€ํ•˜๋ฅผ ์ฆ๊ฐ€์‹œํ‚จ๋‹ค. ๋‘ ๋ฒˆ์งธ, ๋™์ ์ธ ์ฑ„๋„์—์„œ ๋น ๋ฅด๊ณ  ํšจ์œจ์ ์œผ๋กœ ๋Œ€์ฒ˜ํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ์„ธ ๋ฒˆ์งธ, ์ด๋Ÿฌํ•œ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค์—์„œ ์„ ํƒ๋œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋“ค์ด ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ์œ„ํ•œ ์ตœ์ ์˜ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ ์•„๋‹ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ๋“ค์€ ๋ฐฐํ„ฐ๋ฆฌ๋กœ ๋™์ž‘ํ•˜๋Š” ๋…ธ๋“œ๋“ค์˜ ํฐ ์—๋„ˆ์ง€ ์†Œ๋ชจ๋ฅผ ์•ผ๊ธฐํ•˜๊ณ  LoRa ๋„คํŠธ์›Œํฌ์˜ ์ฑ„๋„์ด ๋™์ ์œผ๋กœ ๋ณ€๊ฒฝ๋˜๋Š” ํ™˜๊ฒฝ์—์„œ ์„ฑ๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์šฐ๋ฆฌ๋Š” ์„œ๋ฒ„์˜ ๋ถ€ํ•˜๋ฅผ ์ตœ์†Œํ™”ํ•˜๋ฉฐ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๋…ธ๋“œ ๊ธฐ๋ฐ˜์˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์ธ NbADR์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ๋…ธ๋“œ ์ธก์—์„œ ์ „์†ก ๋ฐ›์€ ๋‹ค์šด๋งํฌ ํŒจํ„ด์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฑ„๋„ ์ƒํ™ฉ์— ๋น ๋ฅด๊ฒŒ ๋Œ€์‘ํ•˜๊ณ , Efficiency of Energy (EoE) ๋ฉ”ํŠธ๋ฆญ์„ ํ™œ์šฉํ•˜์—ฌ ํšจ์œจ์ ์ธ ์—๋„ˆ์ง€ ์†Œ๋ชจ๋ฅผ ์œ„ํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ ํƒํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” EoE ๊ธฐ๋ฐ˜์œผ๋กœ ์„ ํƒํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ํšจ์œจ์„ฑ์„ ๋ถ„์„ํ•˜๊ณ , ๊ด‘๋ฒ”์œ„ํ•œ ์‹คํ—˜์„ ์ง„ํ–‰ํ•œ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, NbADR์€ ๊ธฐ์กด์˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค๊ณผ ๋น„๊ตํ•˜์—ฌ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ ์ธก๋ฉด์—์„œ ํšจ๊ณผ์ ์ด๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ, NbADR์€ ๊ธ‰๊ฒฉํ•˜๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š” ์ฑ„๋„ ํ™˜๊ฒฝ์—์„œLoRa ๋„คํŠธ์›Œํฌ์˜ ์ฒ˜๋ฆฌ๋Ÿ‰์„ ๋ณด์žฅํ•˜๊ณ  ๋…ธ๋“œ ๊ฐ„ ๊ณตํ‰์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค.Chapter 1 Introduction 1 Chapter 2 Related Work 4 Chapter 3 Preliminaries 7 3.1 LoRa/LoRaWAN 7 3.2 Transmission Parameters 8 3.3 ADR Mechanism 9 Chapter 4 Channel Modeling 10 4.1 Loss 10 4.2 Collision 12 Chapter 5 Node-based ADR Mechanism 14 5.1 Approach for Energy Efficiency 15 5.2 Node-based ADR Mechanism (NbADR) 17 Chapter 6 Evaluation 21 6.1 Simulation Settings 22 6.2 Simulation Results 23 Chapter 7 Conclusion 33 Bibliography 35Maste

    An efficient adaptive data-link-layer architecture for LoRa networks

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    LoRa is one of the most popular low-power wireless network technologies for implementation of the Internet of Things, with the advantage of providing long-range communication, but lower data rates, when compared with technologies such as Zigbee or Bluetooth. LoRa is a single-channel physical layer technology on top of which LoRaWAN implements a more complex multi-channel network with enhanced functionalities, such as adaptive data rate. However, LoRaWAN relies on expensive hardware to support these functionalities. This paper proposes a LoRa data-link-layer architecture based on a multi-layer star network topology that adapts relevant LoRa parameters for each end node dynamically taking into account its link distance and quality in order to balance communication range and energy consumption. The developed solution is comprised of multiple components, including a LoRa parameter calculator to help the user to configure the network parameters, a contention-free MAC protocol to avoid collisions, and an adaptive spreading factor and transmission power mechanism. These components work together to ensure a more efficient use of the chosen ISM band and end node resources, but with low-cost implementation and operation requirements.This research was funded by FEDER through COMPETE2020โ€”Programa Operacional Competitividade e Internacionalizaรงรฃo (POCI) grant number POCI-01-0145-FEDER-028247 and by FCTโ€”Fundaรงรฃo para a Ciรชncia e Tecnologia within the R&D Units Project Scope: UIDB/00319/202

    Energy Efficient Uplink Transmissions in LoRa Networks

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    LoRa has been recognized as one of the most promising low-power wide-area (LPWA) techniques. Since LoRa devices are usually powered by batteries, energy efficiency (EE) is an essential consideration. In this paper, we investigate the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. Specifically, our objective is to maximize the corresponding EE by jointly exploiting user scheduling, spreading factor (SF) assignment, and transmit power allocations. To solve them efficiently, we first propose a suboptimal algorithm, including the low-complexity user scheduling scheme based on matching theory and the heuristic SF assignment approach for LoRa users scheduled on the same channel. Then, to deal with the power allocation, an optimal algorithm is proposed to maximize the SEE. To maximize the MEE of LoRa users assigned to the same channel, an iterative power allocation algorithm based on the generalized fractional programming and sequential convex programming is proposed. Numerical results show that the proposed user scheduling algorithm achieves near-optimal EE performance, and the proposed power allocation algorithms outperform the benchmarks. ยฉ 2020 IEEE

    Minimum throughput maximization in LoRa networks powered by ambient energy harvesting

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    In this paper, we investigate the uplink transmissions in low-power wide-area networks (LPWAN) where the users are self-powered by the energy harvested from the ambient environment. Demonstrating their potential in supporting diverse Internet-of-Things (IoT) applications, we focus on long range (LoRa) networks where the LoRa users are using the harvested energy to transmit data to a gateway via different spreading codes. Precisely, we study the throughput fairness optimization problem for LoRa users by jointly optimizing the spreading factor (SF) assignment, energy harvesting (EH) time duration, and the transmit power of LoRa users. First, through examination of the various permutations of collisions among users, we derive a general expression of the packet collision time between LoRa users, which depends on the SFs and EH duration requirements. Then, after reviewing prior SF allocation work, we develop two types of algorithms that either assure fair SF assignment indeed purposefully `unfair' allocation schemes for the LoRa users. Our results unearth three new findings. Firstly, we demonstrate that, to maximize the minimum rate, the unfair SF allocation algorithm outperforms the other approaches. Secondly, considering the derived expression of packet collision between simultaneous users, we are now able to improve the performance of the minimum rate of LoRa users and show that it is protected from inter-SF interference which occurs between users with different SFs. That is, imperfect SF orthogonality has no impact on minimum rate performance. Finally, we have observed that co-SF interference is the main limitation in the throughput performance, and not the energy scarcity
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