Decoding Superposed LoRa Signals

Rachkidy, Nancy El; Guitton, Alexandre; Kaneko, Megumi

doi:10.1109/lcn.2018.8638253

Cited by 41 publications

(40 citation statements)

References 7 publications

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“…In research [12], a decoding technique for LoRa signals was used using a decoding algorithm with two slightly desynchronized superposed LoRa Signals. furthermore, this decoding Algorithm technique is used to increase the effectiveness of sending data e.g, Throughput.…”

Section: A Chirp Lora Signalmentioning

confidence: 99%

Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data

Adi¹,

Kitagawa²

2019

IJACSA

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This research discusses how to build and analyze a 915 MHz Long Range (LoRa) E32 Frequency-based Node Sensor network with a Micro Sensor with 3 sensor outputs produced i.e, Temperature (DegC), Air Pressure (hPa), and Humidity (%). therefore, This research succeeded in making a sensor node using the LoRa E32 915 MHz using a mini type ATmega 328p microcontroller with a 3.7 volt, 1000 mAh battery. The display on the receiver uses an 8X2 LCD which will output 3 sensor data outputs. furthermore, the result and analysis of this research are how to analysis of the LoRa Chirp Signal, furthermore, LoRa Chirp Signal obtained from the Textronix Spectrum analyzer in realtime, Quality of Service (QoS), Receive Signal Strength Indicator (RSSI) (-dBm), uplink and downlink data on the Internet Server. Furthermore, The Micro Sensor Graph Output will be displayed on the application server with a sensor data graph. In this research Application Server used is Thingspeak from Mathworks. Keywords-Long range; microcontroller; internet of things; quality of service; micro sensor(

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Section: A Chirp Lora Signalmentioning

confidence: 99%

Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data

Adi¹,

Kitagawa²

2019

IJACSA

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“…The proposed algorithm was shown to provide significant performance enhancements in terms of achievable throughput, for different SF levels. However, the algorithm in [20] was solely designed to handle two superposed LoRa signals and we did not consider any MAC protocol.…”

Section: Introductionmentioning

confidence: 99%

Collision Resolution Protocol for Delay and Energy Efficient LoRa Networks

Rachkidy

Guitton

Kaneko

2019

IEEE Trans. on Green Commun. Netw.

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Future 5G and Internet of Things (IoT) applications will heavily rely on long-range communication technologies such as low-power wireless area networks (LPWANs). In particular, LoRaWAN built on LoRa physical layer is gathering increasing interests, both from academia and industries, for enabling low-cost energy efficient IoT wireless sensor networks for, e.g., environmental monitoring over wide areas. While its communication range may go up to 20 kilometers, the achievable bit rates in LoRaWAN are limited to a few kilobits per second. In the event of collisions, the perceived rate is further reduced due to packet loss and retransmissions. Firstly, to alleviate the harmful impacts of collisions, we propose a decoding algorithm that enables to resolve several superposed LoRa signals. Our proposed method exploits the slight desynchronization of superposed signals and specific features of LoRa physical layer. Secondly, we design a full MAC protocol enabling collision resolution. The simulation results demonstrate that the proposed method outperforms conventional LoRaWAN jointly in terms of system throughput, energy efficiency as well as delay. These results show that our scheme is well suited for 5G and IoT systems, as one of their major goals is to provide the best trade-off among these performance objectives.

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“…In order to improve the LoRa system performance, a number of works have proposed resource optimization methods [8][9][10]. However, most papers so far have assumed a perfect orthogonality among SFs.…”

Section: Introductionmentioning

confidence: 99%

“…Although the issue of inter-SF interferences was highlighted, it was ignored in their proposed solution. In [10], a method for decoding superposed LoRa signals using the same SF was proposed.…”

Section: Introductionmentioning

confidence: 99%

Spreading Factor Allocation Strategy for LoRa Networks Under Imperfect Orthogonality

Amichi

Kaneko

Rachkidy

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Low-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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Decoding Superposed LoRa Signals

Cited by 41 publications

References 7 publications

Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data

Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data

Collision Resolution Protocol for Delay and Energy Efficient LoRa Networks

Spreading Factor Allocation Strategy for LoRa Networks Under Imperfect Orthogonality

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