Designing and implementing SFMAC: A MAC protocol for LoRa networks for efficient use of unlicensed bands

Master thesis (2020)

Authors

M.T. Blanco Abad Electrical Engineering, Mathematics and Computer Science

Contributors

Ranga Rao Venkatesha Prasad Embedded Systems - EEMCS (supervisor 1)
N. KOUVELAS (supervisor 1)
A.J. van Genderen Computer Engineering - EEMCS (supervisor 2)
Vijay Rao Cognizant Technology Solutions (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2020 Teresa Blanco Abad
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Published Date

27-11-2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Long Range Wide Area Networks (LoRaWAN) offer easy deployment, robustness against interference, and operational longevity to energy constrained IoTdevices which communicate in a best-e_ort fashion in extended ranges. However, the simple (ALOHA-like) design of the MAC layer leads to packet collisions in dense LoRaWAN deployments with high traffic loads. To achieve scalability above a few hundreds of devices, time division is not an option, since LoRaWAN is asynchronous regarding communication. Further, feedback mechanisms are discouraged due to duty cycle limitations. In this document, we propose Spreading Factor MAC (SFMAC); a distributed and energy efficient MAC protocol for LoRaWAN, wherein {for the _rst time to the best of our knowledge{ high-SF channels are dedicated strictly to Channel Sensing (CS), while low-SF channels are focused on data-transmission. The Capture E_ect (CE) phenomena that is manifested in the PHY layer is extensively evaluated on-_eld and embodied in the SFMAC operating principle. The dedicated high-SF sensing allows e_ective revealing of hidden devices' transmissions without a_ecting the low-SF tra_c. We showcase the impact of SFMAC in scalability by designing a realistic implementation of the mechanism in ns-3. We report a x2.08 improvement in channel utilization and x2 goodput compared to LoRaWAN, without substantially increasing complexity.