Amalinda Gamage

Publications | Talks | Teaching | Service

Hello, I'm Amalinda from Sri Lanka 🇱🇰. ආයුබෝවන්! (āyubōwan!)— a warm wish for a long and prosperous life in Sinhalese.

I'm a Research Fellow with NTU, SG. Central to my research is spectral optimization, specifically in the implementation of physical layer techniques that enhance the coexistence & fairness of LPWANs. My current work is focused on bringing improvements to LoRa—a low-power Long Range communication protocol for the Internet of Things.

My work LMAC has been adopted as an industry standard by the LoRa Alliance. It marks the first industry-academia collaboration of the LoRa Alliance to be recognized as a technical recommendation— a collaboration between Semtech, France (patent holder of LoRa), and NTU, SG. Since LMAC is enabled by default in the official LoRaWAN library, it will live inside millions of LoRaWAN devices worldwide. For these contributions, I was named a 2023 Honorees of the LoRa Alliance Contribution Award at LoRaWAN Live'24, shared by contributors who advanced the LoRaWAN standard globally.

I earned a Ph.D. degree in Computer Science from NTU, SG and my Bachelor's degree in Electronic Engineering with a first-class honors from SHU, UK. I learned the ABCs of research and much more from Prof. Mo Li, my PhD mentor. Prior to joining NTU, I was a lecturer at both SLIIT and UNIVOTEC in Sri Lanka. I am also an elected member of The Institution of Engineers Singapore (IES), a signatory of The Washington Accord.

[Summary.] SateRIoT enables reliable IoT connectivity in rural areas by complementing satellite communication with LoRa. It experimentally demonstrates the temporal and spatial challenges of satellite links and effectively mitigates their impact on network performance through a bursty link model and a multi-hop flooding protocol. SateRIoT significantly improves overall network energy efficiency and latency, and it is implemented using cost-effective COTS hardware.

[Summary.] My Ph.D. work, LMAC, enabling CSMA for LoRa, has become an industry standard. In 2022, LMAC was proposed to the LoRa Alliance Technical Committee and the CSMA Task Force (CSMA-TF) was established as a result. Members of CSMA-TF worked closely to develop optimal methods to enable CSMA for LoRaWAN through simulations, experiments while sharing expertise. Modifications were nade to LMAC, such as the removal of interligant channel hopping, to ensure global regulatory compliance. Subsequently, the CSMA-TF presented TR-013 to the LoRa Alliance Technical Committee. It was voted on and accepted by the TC members in June 2023 and thereafter became part of the LoRaWAN standard. This marked the first industry-academia collaboration of the LoRa Alliance that resulted in a Technical Recommendation —a collaboration between Semtech, France, and NTU, Singapore. For this collaboration, myself and my PhD mentor (Prof. Mo Li) were recognized as 2023 Honorees of LoRa Alliance Contribution Award cohort at LoRaWAN Live'24 in Germany by the LoRa Alliance (PR).

Since January 2024, TR-013 has been integrated by default with the official LoRaWAN library. Consequently, LMAC is now embedded in millions of LoRaWAN devices, enhancing reliability and spectral efficiency. Thank you, Semtech and LoRa Alliance, for this wonderful collaboration!

[Summary.] This work extends LMAC, originally published in MobiCom '20. The extension examines several additional aspects of LoRa CSMA, such as quantifying the limitations of RSS-LBT, how LMAC enhances weak LoRa transmissions, the impact of gradual adoption and coexistence of CSMA-enabled LoRa alongside ALOHA, details about global regulatory implications, and finally, how to comply.

Project Website

[Summary.] This work implements collision avoidance across large-scale LoRa networks. CSMA is a technique used by many wireless protocols to avoid collisions. However, LoRa modulation is unique. A single LoRa channel can accommodate multiple frames simultaneously. LoRa frames also have the ability to traverse underneath the noise floor. Therefore, we need a CSMA protocol that doesn't debilitate LoRa's key advantages. LMAC is a simple protocol that does just that reliably with an extremely small energy overhead.

Project Website

[ABSTRACT] Long Range (LoRa) is a Low-power Wide-area Network technology designed for the Internet of Things. In recent years, it has gained significant momentum among industrial and research communities. Patented by Semtech, LoRa makes use of chirp spread spectrum modulation to deliver data with promises of long battery life, far-reaching communication distances, and a high node density at the cost of data rate. In this article, we conduct a series of experiments to verify the claims made by Semtech on LoRa technology. Our results show that LoRa is capable of communicating over 10km under line-of-sight environments. However, under non-line-of-sight environments, LoRa’s performance is severely affected by obstructions such as buildings and vegetations. Moreover, the promise of prolonged battery life requires extreme tuning of parameters. Last, a LoRa gateway supports up to 6,000 nodes with PRR requirement of >70%. This study also explores the relationship between LoRa transmission parameters and proposes an algorithm to determine optimal settings in terms of coverage and power consumption under non-line-of-sight environments. It further investigates the impact of LoRa Wide-area Networks on energy consumption and network capacity along with implementation of a LoRa medium access mechanism and possible gains brought forth by implementing such a mechanism.

[ABSTRACT] In areas where the habitats of elephants and humans are rapidly encroaching on each other, real-time monitoring of the elephants’ locations has the potential to drastically improve the co-existence of elephants and humans, resulting in reduced deaths in both groups. However, as tagging (using GPS collars) elephants to obtain such location information is difficult and costly, it is important to ensure very long lifetimes of the tags, which can only be achieved using energy harvesting.
In this paper, we present a kinetic energy harvester that uses magnetic levitation and ferro fluid bearings to generate energy from an elephant’s movements. In order to determine the feasibility of using this kinetic energy harvester for powering the tags on elephants, we obtained real acceleration data collected from an Asian elephant over a 10 day period, and this data was then used to tune the system to maximize the harvested energy. Using experimentally validated analytical and simulation models, and the actual elephant acceleration data, we find that our prototype can generate 88.91J of energy per day. This energy is not only sufficient to power the tags to acquire and transmit locations 24 times a day to a distance of 114km (line of sight), but provides a surplus of at least 35.40J, which can be used to increase the frequency of position updates or to support alternative communication options such as GPRS. Therefore, this shows the viability of long-term tracking of elephants.