Dynamic Spreading Factor and Power Allocation of LoRa Networks for Dense IoT Deployments

Babaki, Jaber; Rasti, Mehdi; Aslani, Rojin

doi:10.1109/pimrc48278.2020.9217283

Cited by 26 publications

(29 citation statements)

References 8 publications

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“…The simulation results indicated that the resource allocation mechanism obtained 80% better performance than the baseline method, while being much less complex. The authors of [115] improved the basic ADR by dynamically designating the radio parameters, SF and TP, and using the OWA operator. This work focuses on increasing the network noise resilience and PDR in dense IoT scenarios through recognition of the nature of OWA decision making and PLR metric, reaching low energy consumption for all channel conditions.…”

Section: B Sensor/iot Device Side 1) Resource Allocationmentioning

confidence: 99%

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

et al. 2022

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Emerging Internet-of-Things (IoT) applications are driving increasing demand for advanced services in wireless networks, prompting the development of new technologies to address the associated challenges. Energy efficiency of IoT standards is a key feature targeted by research efforts and industrial activities, leading to an extensive and growing number of innovative solutions. Low Power Wide Area Networks (LPWANs) define a class of wireless communication technologies seen as highly relevant for future IoT development given its long communication range, low-cost devices and interesting energy management. Long Range Wide Area Network (LoRaWAN) is acknowledged to be the dominant IoT communication technology. It has allowed broad deployment and unlocked new IoT applications such as smart cities, asset tracking, etc. This article provides a comprehensive tutorial on the LoRa standard, and surveys existing solutions, hot topics and future insights for building energy efficient IoT infrastructures and IoT devices. Indeed, energy efficiency is one of the key factors for successful and sustainable deployments of IoT applications. More precisely, this article discusses how to meet LoRa/LoRaWAN energy efficiency across physical layer, medium access control layer, and network layer. Next, extensive pioneering solutions from related literature are compared and assessed. Finally, insightful conclusions are drawn, and open problems are listed at the end of this article.

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Section: B Sensor/iot Device Side 1) Resource Allocationmentioning

confidence: 99%

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

et al. 2022

View full text Add to dashboard Cite

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“…Babaki et al [88] enhanced the default resource allocation algorithm, i.e. ADR, by dynamically designating the radiorelated parameters, SF and TP, and applying the OWA operator.…”

Section: Multiple Parametermentioning

confidence: 99%

A Survey on Long-Range Wide-Area Network Technology Optimizations

et al. 2021

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Long-Range Wide-Area Network (LoRaWAN) enables flexible long-range service communications with low power consumption which is suitable for many IoT applications. The densification of LoRaWAN, which is needed to meet a wide range of IoT networking requirements, poses further challenges. For instance, the deployment of gateways and IoT devices are widely deployed in urban areas, which leads to interference caused by concurrent transmissions on the same channel. In this context, it is crucial to understand aspects such as the coexistence of IoT devices and applications, resource allocation, Media Access Control (MAC) layer, network planning, and mobility support, that directly affect LoRaWAN's performance. We present a systematic review of state-of-the-art works for LoRaWAN optimization solutions for IoT networking operations. We focus on five aspects that directly affect the performance of LoRaWAN. These specific aspects are directly associated with the challenges of densification of LoRaWAN. Based on the literature analysis, we present a taxonomy covering five aspects related to LoRaWAN optimizations for efficient IoT networks. Finally, we identify key research challenges and open issues in LoRaWAN optimizations for IoT networking operations that must be further studied in the future.

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“…The last thing is about ADR Response, if successful then ADR Success, and go to the un-schedule ADR process. The ADR algorithm is often used for Low Data Rate data such as that of LoRa and together with Spreading Factor analysis (6-12) [15],] [20], [23].…”

Section: B Adaptive Data Rate (Adr) Mechanism Approachmentioning

confidence: 99%

Integrating Cost-231 Multiwall Propagation and Adaptive Data Rate Method for Access Point Placement Recommendation

Mukti¹,

Adi²,

Prasetya³

et al. 2021

IJACSA

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A new approach has been developed to provide an overview about signal behavior in indoor environments using Cost-231 Multiwall Model (Cost-231 MWM) and Adaptive Data Rate (ADR) method. This approach used as a reference for access point (AP) placement for campus building. The Cost-231 MWM plays a role in estimating the measured power received by user (usually called as Received Signal Strength Indicator/RSSI) by considering the existence of obstacles around the transmitter (AP). We used Institut Asia Malang environments as the case study and gave some recommendations for AP placement: ten optimal placements for the first, third and fourth floor, also seven optimal placements for the second floor. These recommendations were based on the RSSI for good and excellent level signal (-50 dBm until -10dBm). This research also uses the Adaptive Data Rate (ADR) mechanism approach to reduce the amount of packet loss (kbps) resulting from obstacles that cause attenuation (-dB). With the Adaptive Data Rate mechanism, it means increasing the number of access points, the signal attenuation (-dB) occurs from the obstacles (Walls) that are penetrated by the Radio Frequency device and causes attenuation (-dB), the more Access points on the Multi-Wall, will allow communication and data transmitting stability.

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Dynamic Spreading Factor and Power Allocation of LoRa Networks for Dense IoT Deployments

Cited by 26 publications

References 8 publications

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

A Survey on Long-Range Wide-Area Network Technology Optimizations

Integrating Cost-231 Multiwall Propagation and Adaptive Data Rate Method for Access Point Placement Recommendation

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