401 research outputs found
np-CECADA: Enhancing Ubiquitous Connectivity of LoRa Networks
No full textLong Range Wide Area Networks (LoRaWAN) offer ubiquitous communications for The Internet of Things (IoT). However, there are many challenges in rolling out LoRaWAN - mainly scalability, energy efficiency, Packet Reception Ratio (PRR), and keeping the channel access as simple as unslotted ALOHA. To this end, we design non-persistent Capture Effect Channel Activity Detection Algorithm (np-CECADA), which is a novel, distributed protocol for the MAC layer of LoRaWAN. It utilizes Channel Activity Detection (CAD), which is a built-in imperfect mechanism for channel sensing and minimal feedback from the gateways. In np-CECADA each device independently adapts backoff times based on the traffic in its vicinity and the transmission power based on the heuristically inferred probability of capturing the channel. To achieve this, first, we carried out an extensive on-field evaluation to measure the effectiveness of CAD and capture effect in LoRa. Using them we designed np CECADA and developed ns-3 modules. Packet Reception Ratio of np-CECADA is 15.74× and 5.13× higher than vanilla LoRaWAN and p-CARMA, respectively. Channel utilization is 11.24× higher compared to LMAC. Further, on a testbed of 30 LoRa devices np-CECADA outperforms LoRaWAN up to 5 times.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Embedded System
Energy Efficient Data Recovery from Corrupted LoRa Frames
No full textHigh frame-corruption is widely observed in Long Range Wide Area Networks (LoRaWAN) due to the coexistence with other networks in ISM bands and an Aloha-like MAC layer. LoRa's Forward Error Correction (FEC) mechanism is often insufficient to retrieve corrupted data. In fact, real-life measurements show that at least one-fourth of received transmissions are corrupted. When more frames are dropped, LoRa nodes usually switch over to higher spreading factors (SF), thus increasing transmission times and increasing the required energy. This paper introduces ReDCoS, a novel coding technique at the application layer that improves recovery of corrupted LoRa frames, thus reducing the overall transmission time and energy invested by LoRa nodes by several-fold. ReDCoS utilizes lightweight coding techniques to pre-encode the transmitted data. Therefore, the inbuilt Cyclic Redundancy Check (CRC) that follows is computed based on an already encoded data. At the receiver, we use both the CRC and the coded data to recover data from a corrupted frame beyond the built-in Error Correcting Code (ECC). We compare the performance of ReDCoS to (i) the standard FEC of vanilla-LoRaWAN, and to (ii) Reed Solomon (RS) coding applied as ECC to the data of LoRaWAN. The results indicated a 54x and 13.5x improvement of decoding ratio, respectively, when 20 data symbols were sent. Furthermore, we evaluated ReDCoS on-field using LoRa SX1261 transceivers showing that it outperformed RS-coding by factor of at least 2x (and up to 6x) in terms of the decoding ratio while consuming 38.5% less energy per correctly received transmission.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Embedded System
LoRa Weather Station
No full textabstract: Communication between the physical and digital world via software, embedded sensors and network connectivity is referred to by the term, the "Internet of Things" (IoT) [1]. The IoT transforms natural objects into "smart devices" to improve accuracy, reduce human intervention, and provide real-time data [1]. Smart weather stations that upload information, including temperature and humidity, to the Internet are already available. However, these products are often expensive and programmed only for single-purpose use. The LoRa Weather Station is a low cost, low power and low maintenance IoT solution that combines Microchip Technology's LoRa RN2903 module along with Mikroelektronika's Weather Click sensor. This report discusses how the LoRa Weather Station was created, primarily focusing on the LoRa gateway setup by a Raspberry Pi local web server. This project was completed by four electrical engineering students in the EEE 488 and 489 Senior Design courses at Arizona State University from Fall 2016 to Spring 2017. Total expenses for the project were 104 (see Appendix C for the Bill of Materials)
Analysis of Remote Sensing approaches for LoRa coverage estimation
No full textLoRa is being widely adopted by industrial communities for its long range, robustness and low power wireless communication capabilities. In fact LoRa is gaining more popularity even amongst the common people as it is an affordable solution and operates in the unlicensed radio spectrum. However, LoRa provides a widely heterogeneous coverage; it can reach hundreds of meters or up to tens of kilometers, depending on the surrounding environment. Determining the coverage of LoRa stations is key to provide a good quality of service. On one hand, the traditional method of expensive measurement campaigns can be employed to estimate LoRa's coverage; but this is impractical due to the large geographical areas involved. On the other hand, popular channel models can be adopted; but many of them are yet to be explored for LoRa or rely entirely on the user predening the type of environment to estimate coverage. Neither of those approach are suitable for thousands of non-expert citizens and organizations around the world looking forward to understanding the coverage of their LoRa stations. The aim of the thesis is to automatically estimate the coverage of LoRa, before the deployment of the gateway and without relying on on-site measurements or the user's perception of the environment. Moreover, the estimation must be carried out in a simple, low cost and low eort approach. Considering that the surrounding environment determines in a fundamental manner, the coverage of wireless technologies including LoRa, we use readily available remote sensing information coming from satellites to estimate the characteristics of an area. In this manner, we free up the user from providing any type of data. Based on this remote sensing approach, the thesis provides two main contributions: First we analyze a group of parametric models (ITU-R 1812 and Okumura Hata model) and determine that the Okumura Hata model is better suited for LoRa. Second we improve the performance of using the basic Okumura Hata model by proposing an automated approach that explores remotely sensed height models and land cover maps to automatically congure channel model parameters. The performance is evaluated based on a relative comparison due to some unknown transmitter setting parameters and assess which algorithm accurately tracks the changes in the real path loss. A validation using a relative comparison approach on 18000+ samples of real LoRa data shows that the modied algorithm gives an improved performance compared to the novel approach in path loss prediction and the ITU model. The modied algorithm could improve the coverage up to a factor of 5 compared to the novel approach in free space ranges. Moreover, in an urban built-up city the modied algorithm could improve the coverage by up to 1.5 km compared to the novel approach.Electrical Engineering | Embedded System
Analysing TDoA Localisation in LoRa Networks
No full textThe IoT contains billions of interconnected devices and is only growing larger by the day. These devices often need to operate for years while keeping mobile objects, such as animals or vehicles, connected to a larger system. Therefore they will be battery-powered, energy efficient and, their position will be tracked. Therefore, connecting these devices requires low-power, long-range communication that can also be used for localisation. Because of the scale of the IoT industry, manufacturing and infrastructure costs need to be considered. The low cost, long range and energy efficiency that is required exempts many wireless communication and localisation solutions such as WiFi, GPS and Bluetooth because they are not as suitable as Low-Power Wide-Area Networks (LPWAN's). LoRa is a LPWAN technology that is both Long-Range and cost effective. Therefore, the objective of this thesis is to use a LoRa network for our localisation algorithms.In this work we show that signal strength data becomes turbulent when communicating over a large, urban area. Therefore we evaluate Time Difference of Arrival (TDoA)-based localisation algorithms, including a novel area-based algorithm that we developed. We evaluate the localisation algorithms on a proprietary LoRa network which also provides a localisation service that we use as a benchmark. We evaluate the performance of the algorithms over a large, mostly urban, region of The Netherlands. Using mobile LoRa devices, we show that for 80\% of cases, our proposed algorithm has a position error less than 925m. We also show that the other localisation methods, including the proprietary localisation service, have a larger maximum position error for the same portion of cases. This work contributes a localisation algorithm that can compete against proprietary geolocation services, such as Sigfox and KPN's services, in many applications.Electrical Engineering | Embedded System
APPLICATION OF LORA IN DATA TRANSFER IN AGRICULTURE
Full text linkAbstract
Da Lat - Lam Dong, one of the localities with strengths in agriculture, especially in the high-tech segment, is being widely applied today. In response to practical needs, the author build an application using Lora network to easily relay data from sensor devices serving agriculture such as: Soil moisture, ambient temperature, PH level, etc. From the collection of data, they will be forwarded to the server system so that they can be used for purposes such as monitoring, automation, and production processes. Lora network is known as an RF (Radio Frequency) modulation technology for low power wide area network with long distance connectivity along with low energy, low bandwidth, so it is suitable for conditions, applications, IoT devices development, low performance time and building smart agricultural system for practical needs being placed locally
LoRa Localisation in Cities with Neural Networks
No full textBillions of wireless devices are interconnected to provide services to manyaspects of life and form The Internet of Things. These devices which areoften battery-powered and energy efficient can benefit greatly from an ac-curate localisation service that does not consume extra energy. Several loc-alisation methods have been developed for Low-Power Wide-Area Networks(LPWANs), with LoRa being of particular interest thanks to its long rangeand cost effectiveness. Time Difference of Arrival (TDoA) is a common wayto find location in a LoRa network which works well in open areas but poorlyin the harsh radio environment of cities. In indoor settings where the radioenvironment is more complicated than outdoor, RSSI fingerprinting tech-niques have been sucessfully used for positioning using WiFi and Bluetooth,with state-of-the-art solutions employing Artificial Neural Networks (ANN).This work aims to provide accurate localisation in an urban LoRa network,using an ANN-based fingerprinting approach. Two publicly available datasets collected in the cities of Utrecht and Antwerp are used to evaluate ourmethod. We show that the ANN model can be trained on these data sets topredict location with mean errors between 411m and 581m. We determinethat the presence of gateways in the fingerprint plays a major role in theANN’s estimation but RSSI information is crucial in improving the accuracy.To realistically compare the ANN approach to TDoA, we train and test theneural network with chronologically split data. Our ANN approach achievesa mean error of 500m with 90% of cases having errors below 1070m. ThisRSSI fingerprinting method is more effective than TDoA at limiting largelocalisation errors in cities.Electrical Engineering | Embedded System
Investigation on Time-of-Arrival Estimationfor the LoRa Network
No full textLoRa (Long Range) is a low-power, long-range and low-cost wireless communication system that can facilitate a wide variety of infrastructures for the Internet of Things (IoT). Current algorithms to locate LoRa tags have a resolution of 100 m in practice, and a question is if that can be improved without changing the tags or adding too much to the gateways (basestations). Conventional delay estimation ranging algorithms extract useful information from the channel frequency response and use this information to estimate delays. In this thesis, three localization techniques are presented: the matched filter, FBCM-MUSIC and TLS-ESPRIT algorithms. Then a multiband architecture is proposed and integrated into the matched filter. These algorithms are implemented in the LoRa system model. The simulations indicate that FBCM-MUSIC and TLS-ESPRIT have better performance than the matched filter in NLOS channels. The results also show that TLS-ESPRIT is more effective and robust compared to MUSIC. The proposed multiband architecture can improve the resolution of TOA estimation and decreases the 90th percentile error by around 40%.Electrical Engineering | Circuits and System
Demo: Lora mesh network experimentation in a city-wide testbed
No full textLoRa is a low-power long-range Internet of Things (IoT) standard that offers remarkable performance, especially in remote rural areas. However the single-hop nature of current LoRa networks, poses significant challenges for urban setups and complex network environments, where several gateways with network access need to be deployed to offer the required connectivity. Towards overcoming the connectivity inefficiency of LoRa in relevant environments, the application of mesh networking has been identified as a candidate solution with rich potential. In this work, we present a LoRa based mesh-networking tool for LoRa mesh experimentation. that is currently applied in testbed of 10 LoRa mesh capable devices across the city area of Volos, Greece. © 2019 Copyright held by the owner/author(s)
Energy Consumption and Scalability of Transmitting Firmware Updates Over LoRa
No full textThe rapid growth of LoRa sensor networks lead to more and more maintenence challenges. One of them is wirelessly updating the firmware, especially for the ones that are hard or dangerous to reach. Is it feasible to do a firmware update over LoRa, and what is its additional power consumption of the wireless sensors? In this thesis a LoRa Class B Firmware Update Over The Air (FUOTA) is implemented and evaluated. Up to 100 end-devices are used to research the scalibilities and power consumption of the end-devices. The focus is mainly on the tranmission of the firmware itself rather than installing the firmware on the end-devices.This study introduces a power consumption model based on measurements of real hardware. After that, experiments are performed to evaluate the packet losses when scaling up the number of end-devices. These experiments show that the setup time increases with the number of end-devices due to the duty cycle restriction of the gateway. Antother experiment, focusing on end-devices that are part of the network but do not need to be updated, shows these end-devices suffer in terms of packets loss due to packet blockings during a firmware update.The extra setup time needed when scaling up the number of end-devices causes higher power consumption when more devices needs to be updates. To reduce the energy consumption during this setup phase, an improvement to the communciation protocol is presentated at the end of this thesis. It reduces the number of times receive windows are opened while nothing is send.Electrical Engineering | Embedded System
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