Performance Determinants in LoRa Networks: A Literature Review

Gkotsiopoulos, Panagiotis; Zorbas, Dimitrios; Douligeris, Christos

doi:10.1109/comst.2021.3090409

Cited by 78 publications

(31 citation statements)

References 115 publications

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“…In this section, the author discusses a few recent survey papers that are pertinent to the study. In this study [66], operations on LoRa-based platforms are examined. Teir behavior is described, and they are categorized based on their technical advancements.…”

Section: Related Workmentioning

confidence: 99%

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Requirements, Deployments, and Challenges of LoRa Technology: A Survey

Kamal

Alam

Sajak

et al. 2023

Computational Intelligence and Neuroscience

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LoRa is an ISM-band based LPWAN communication protocol. Despite their wide network penetration of approximately 20 kilometers or higher using lower than 14 decibels transmitting power, it has been extensively documented and used in academia and industry. Although LoRa connectivity defines a public platform and enables users to create independent low-power wireless connections while relying on external architecture, it has gained considerable interest from scholars and the market. The two fundamental components of this platform are LoRaWAN and LoRa PHY. The consumer LoRaWAN component of the technology describes the network model, connectivity procedures, ability to operate the frequency range, and the types of interlinked gadgets. In contrast, the LoRa PHY component is patentable and provides information on the modulation strategy which is being utilized and its attributes. There are now several LoRa platforms available. To create usable LoRa systems, there are presently several technical difficulties to be overcome, such as connection management, allocation of resources, consistent communications, and security. This study presents a thorough overview of LoRa networking, covering the technological difficulties in setting up LoRa infrastructures and current solutions. Several outstanding challenges of LoRa communication are presented depending on our thorough research of the available solutions. The research report aims to stimulate additional research toward enhancing the LoRa Network capacity and allowing more realistic installations.

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Section: Related Workmentioning

confidence: 99%

“…In this study [ 66 ], operations on LoRa-based platforms are examined. Their behavior is described, and they are categorized based on their technical advancements.…”

Section: Related Workmentioning

confidence: 99%

Requirements, Deployments, and Challenges of LoRa Technology: A Survey

Kamal

Alam

Sajak

et al. 2023

Computational Intelligence and Neuroscience

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show abstract

“…[39] Surveys the available tools for simulating LoRa networks in NS-3 network simulator. [40] Presents an overview on LoRa networks considering PHY layer characteristics, deployment and hardware features, end device transmission settings, and MAC protocols. [41] Provides experimental performance evaluation of ADR enhancements in a mobile node scenario.…”

Section: B Motivation and Contributionsmentioning

confidence: 99%

A Survey on Chirp Spread Spectrum-based Waveform Design for IoT

Azim¹,

Bazzi²,

Shubair³

et al. 2022

Preprint

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<p>Long Range (LoRa) is one of the most promising and widespread chirp spread spectrum (CSS)-based physical (PHY) layer technique for low-power wide-area networks (LPWANs). Using different spreading factors, LoRa can attain different spectral/energy efficiencies, and can target multitude of Internet-of-Thing (IoT) applications. However, one of the limiting factors for LoRa is the low bit rate. Little to no effort has been made in order to improve the achievable rate of LoRa, until recently, when a number of CSS-based PHY layer LoRa alternative are proposed for LPWANs. In this survey, for the first time, we present a comprehensive waveform design of these CSS-based schemes that have been proposed between 2019 to 2022. In total, fifteen alternatives to LoRa are compared. Other survey articles related to LoRa mostly tackle different issues, such as LoRa networking, LoRa deployment in massive IoT networks, and LoRa architectures, etc. This survey, on the other hand, comprehensively elucidates the waveform design of LoRa alternatives. The CSS schemes studied in this survey are divided into single chirp, multiple chirp, and index modulation based on the multiplexing pattern of the chirps. Complete transceiver architecture of these CSS schemes is studied, and performance is evaluated in terms of energy efficiency (EE), spectral efficiency (SE), bit-error rate (BER) performance in additive white Gaussian noise, BER in the presence of phase and frequency offsets. It has been observed that the EE, SE and robustness against the offsets is primarily linked to transmit symbol frame structure. The public versions of the MATLAB codes for the CSS schemes studied in this survey shall be provided to promote reproducible research.</p>

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“…LoRa [15,16] achieves super anti-interference and long-distance transmission through spread spectrum modulation technology. This technology trades bandwidth for sensitivity [17] and is used in communication technologies such as WiFi [18,19] and Zigbee [20]. LoRa modulation is characterized by maximizing sensitivity, even approaching the limit of Shannon's theorem [21].…”

Section: Introductionmentioning

confidence: 99%

Optimization of LoRa SF Allocation Based on Deep Reinforcement Learning

Zhong

Ning

Wang

et al. 2022

Wireless Communications and Mobile Computing

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LoRa is an IoT communication technology that realizes ultra-long-distance transmission through spread spectrum modulation. However, its ultra-long-distance transmission also sacrifices the corresponding rate, and data conflicts are prone to occur when the number of nodes is large. In this article, we investigate various types of data collisions in LoRa wireless work, most of which are affected by Spreading Factor (SF) assignment. At present, the distribution of the SF for LoRa in the industry is mostly based on Min-airtime and Min-distance. In the case of a large number of nodes, the data collision between nodes will increase sharply. This paper proposes a SF redistribution scheme under limited network resources, in order to improve the terminal capacity of the LoRa gateway. First, the problem of minimizing the data collision rate without expanding gateway or network resources is presented. Specifically, the reallocation of SF with increasing number of terminals is studied. Finally, considering the randomness of the data sent by the terminal, SF redistribution schemes based on deep reinforcement learning (DRL) are developed. The simulation results show that the collision rate of the proposed SF redistribution scheme is nearly 30% lower than Min-airtime and Min-distance, and its total energy consumption is close to Min-distance. Therefore, the proposed SF redistribution scheme can effectively improve the gateway capacity of LoRa wireless network.

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Performance Determinants in LoRa Networks: A Literature Review

Cited by 78 publications

References 115 publications

Requirements, Deployments, and Challenges of LoRa Technology: A Survey

Requirements, Deployments, and Challenges of LoRa Technology: A Survey

A Survey on Chirp Spread Spectrum-based Waveform Design for IoT

Optimization of LoRa SF Allocation Based on Deep Reinforcement Learning

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