3 research outputs found

    Optimiser l'รฉquitรฉ dans les rรฉseaux LoRaWAN

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    International audienceNous prรฉsentons un modรจle d'optimisation pour la planification d'un rรฉseau LoRa avec une passerelle, dont le but est de dรฉterminer les bornes des zones de facteur d'รฉtalement (SF) de maniรจre ร  maximiser le taux de livraison des paquets (PDR) minimum des noeuds du rรฉseau. Grรขce ร  notre modรจle, nous amรฉliorons le PDR minimum de plus de 13% en comparaison de l'allocation usuelle des SFs basรฉe sur un seuil signal sur bruit (SNR). Nous รฉtudions enfin le compromis entre temps de rรฉsolution et prรฉcision de la solution afin de valider notre modรจle lorsque la densitรฉ des noeuds augmente

    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

    Spreading Factor Allocation Strategy for LoRa Networks under Imperfect Orthogonality

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    International audienceLow-Power Wide-Area Network (LPWAN) based on LoRa physical layer is envisioned as one of the most promising technologies to support future Internet of Things (IoT) systems. LoRa provides flexible adaptations of coverage and data rates by allocating different Spreading Factors (SFs) to end-devices. Although most works so far had considered perfect orthogonality among SFs, the harmful effects of inter-SF interferences have been demonstrated recently. Therefore in this work, we consider the problem of SF allocation optimization under co-SF and inter-SF interferences, for uplink transmissions from end-devices to the gateway. To provide fairness, we formulate the problem as maximizing the minimum achievable average rate in LoRa, and propose a SF allocation algorithm based on matching theory. Numerical results show that our proposed algorithm enables to jointly enhance the minimal user rates, network throughput and fairness, compared to baseline SF allocation methods
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