LoRa Scalability: A Simulation Model Based on Interference Measurements

Haxhibeqiri, Jetmir; Abeele, Floris Van den; Moerman, Ingrid; Hoebeke, Jeroen

doi:10.3390/s17061193

Cited by 226 publications

(117 citation statements)

References 14 publications

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“…For this, we prepared a simulation environment for scalability tests. The simulator is a Python [27]. The transmissions are done randomly from different transmissions.…”

Section: B Simulation Methodsmentioning

confidence: 99%

LoRa indoor coverage and performance in an industrial environment: Case study

Haxhibeqiri

Karaağaç

Abeele

et al. 2017

2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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118

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Abstract-LoRa is a long range, low power, low bit rate, single hop wireless communication technology. It is intended to be used for Internet of Things (IoT) networks, where devices are battery powered and limited bandwidth is needed. In combination with its scalability and the low end device price, LoRa is a candidate technology for low bandwidth industrial applications with a high number of communication devices spread across large areas. The use case for this paper is taken from the flower industry, where a large number of trolleys need to communicate with a server during their movement across the auction floor area. Once trolleys are outside of the auction floor they can use the public LoRaWAN network to communicate with the server, without switching communication technology. The LoRaWAN network consists of multiple end nodes and a single gateway per cell, acting as a transparent bridge between the end nodes and the network server. The measurements show that with a single LoRa gateway we can cover an indoor area of around 34000m2 only with spreading factor 7, while for spreading factor 12 the total covered area will be even higher. Also, the area outside the factory is covered when switching to spreading factor 12. We also show that the number of nodes (trolleys) that can be served by a gateway in such a case can be as high as 6000.

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“…For this, we prepared a simulation environment for scalability tests. The simulator is a Python [27]. The transmissions are done randomly from different transmissions.…”

Section: B Simulation Methodsmentioning

confidence: 99%

LoRa indoor coverage and performance in an industrial environment: Case study

Haxhibeqiri

Karaağaç

Abeele

et al. 2017

2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

Self Cite

118

View full text Add to dashboard Cite

show abstract

“…By using 125-kHz channel bandwidth in the LoRaWAN network with the same number of end devices to avoid collision between the transmitted packets. In [12], the authors show a study for the uplink traffic in LoRaWAN where the packet delivery ratio decreases exponentially with increasing the number of end nodes in the network. Mikhaylov et al [8] present an estimation of the throughput of LoRa technology, considering the time on air of the packet transmission.…”

Section: Related Workmentioning

confidence: 99%

“…To calculate the probability of collision Pc n 2 ðpÞ n 1 ðpÞ between n 1 ðpÞ and n 2 ðpÞ at the LoRaWAN gateway, given that n 1 ðpÞ represent the node of interest. If c n 2 ðpÞ n 1 ðpÞ indicates the collision, based on (12), the collision case is defined as follows:…”

Section: Mathematical Analysismentioning

confidence: 99%

“…where the random variable T n 2 ðpÞ is the summation of multiple uniform random variables see (12). All packets are sorted by arrival time to find the collided packets.…”

Section: Mathematical Analysismentioning

confidence: 99%

“…After adding the T Guard , we modify equation (12) to have the new start time packet T n b new as follows:…”

Section: Mathematical Analysismentioning

confidence: 99%

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IoT scheduling for higher throughput and lower transmission power

2020

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The massive increase in the Internet of Things (IoT) has brought a diverse long-range, low-power, and low bit-rate wireless network technologies. The LoRa a low-power wide area network (LPWAN) gained popularity as radio technology for the realization of many IoT applications. LoRa is typically employed together with LoRaWAN MAC protocol and operates in the license-free ISM bands. LoRa networks have an issue with scalability when the number of end nodes connected to one network is larger than the shared number of channels, that causes a collision and packets loss through receiving a wide range of different message sizes from various application. In this paper, we describe an accurate and efficient way confirmed by simulation to calculate the probability of collision rate and packet loss in LPWANs under various circumstances. Moreover, based on the LoRaWAN specification, we consider a dense network deployment of IoT devices. In the event of collisions, our proposed algorithms is classified to two approaches. Firstly a time scheduling algorithm is proposed for LoRaWAN networks that consist of devices supporting LoRaWAN class C mode for synchronization in the beginning between the gateway and the end nodes. Afterwards these devices switch to class A to significantly decrease the collision and to enhance scalability by assigning a Guard Time to each end node. Gateway acknowledgment (ACK) messages to the end nodes are used through class C. Secondly, we also propose a distance spreading factor algorithm according to the distance of the end nodes from the gateway to reduce the probability of collision. Furthermore, many of these devices are battery powered, therefore low power consumption is required.

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ND‐ADR: Nondestructive adaptive data rate for LoRaWAN Internet of Things

Lodhi

Wang

Farhad

2022

Int J Communication

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Typically, LoRaWAN utilizes an adaptive data rate (ADR) for resource assignment (e.g., spreading factor and transmit power) to a large number of end devices (EDs). However, the slow adaptation of the spreading factor and transmitting power strategy makes the ADR vulnerable to destructive concurrent transmissions, resulting in massive packet collision. Therefore, this paper analyzes the impact of massive concurrent transmissions and proposes a novel "nondestructive adaptive data rate (ND-ADR)" approach to address the packet collision problem. The proposed ND-ADR aims to monitor the destructive concurrent transmissions proactively and mitigate them by allocating nondestructive transmission time to EDs. The proposed ND-ADR ensures high robustness and reliability by reducing the chances of destructive transmissions and retransmissions. Results show that the proposed ND-ADR outperforms the existing state-of-the-art ADRs in packet success ratio and energy consumption.adaptive data rate, Internet of Things (IoT), Long Range (LoRA), LoRaWAN, spreading factor | INTRODUCTIONMassive sensor networks are the main engine to driving the Internet of Things (IoT) from environmental, home, military, health, and other commercial areas. 1 Battery-operated sensors are used across all industries 2 to gather a massive amount of critical data. There is always a big challenge in wireless communication related to power consumption and communication. There are short-range technologies like WiFi, Zigbee, and Bluetooth in the pool of wireless technologies. Cellular networks (e.g., 3G, 4G, and 5G) are available to meet the market requirements based on the bandwidth and long-range. However, these short-range (e.g., WiFi, Zigbee, and Bluetooth) and cellular technologies cannot fulfill the need for lower power consumption over a long distance. 3 Low power wide area network (LPWAN) is a new type of wireless technology designed to transmit small data over long-range using low power, low bandwidth, and low bit rate (e.g., 0.3 to 50 kbit/s) needed for robust IoT networks.There are numbers of competing technologies in the LPWAN, such as narrowband-IoT (NB-IoT), 4 Long Range (LoRa), 5 RPMA, 6 Sigfox, 7 and weightless. 8 Therefore, the following listed unique features of LPWAN technologies make it suitable for machine-to-machine and IoT needs.(i) Long-range: LPWAN covers the long area over 2 km in an indoor area, and up to 10 km in a line of sight (LoS). 9

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LoRa Scalability: A Simulation Model Based on Interference Measurements

Cited by 226 publications

References 14 publications

LoRa indoor coverage and performance in an industrial environment: Case study

LoRa indoor coverage and performance in an industrial environment: Case study

IoT scheduling for higher throughput and lower transmission power

ND‐ADR: Nondestructive adaptive data rate for LoRaWAN Internet of Things

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