Laura Marie Feeney’s research while affiliated with Uppsala University and other places

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Publications (48)


Cross-Technology Clear Channel Assessment for Low-Power Wide Area Networks
  • Conference Paper

November 2019

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15 Reads

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6 Citations

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Laura Marie Feeney

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Martin Jacobsson

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Per Gunningberg

Fig. 1: Signals from LoRa with (SF7, BW 125) kHz and IEEE 802.15.4 FSK overlapping for 20 ms on the same CF.
Fig. 2: Signals from LoRa with (SF12, BW 125) kHz and IEEE 802.15.4 FSK overlapping for 130 ms on the same CF.
Fig. 3: Two TI CC1310 Launchpad nodes act as sender and receiver and a Netblocks LoRa node acts as interferer. The three nodes are connected via an RF combiner.
Fig. 4: PRR measurements in the testbed (LoRa SF12 CF=868.3 MHz) at the IEEE 802.15.4 sender and receiver. Each diagonal contains PRR measurements having the same SNIR. The measurement strategy focuses on regions where the PRR transitions from 0 to 100%. If the PRR is 100% for a given signal and interference strength, then it will be 100% for all higher signal strengths and all lower interference strengths.
Fig. 8: MLP classifier

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Cross-technology Clear Channel Assessment for Low-Power Wide Area Networks
  • Preprint
  • File available

August 2019

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983 Reads

Due to their popularity, large coverage areas, and diversity of radio technologies, Low Power Wide Area Networks (LPWAN) will experience high levels of cross-technology interference. In this work, we investigate the impact of LoRa interference on IEEE 802.15.4 (Wi-SUN) networks. Using hardware experiments , we characterize the interaction between these two very different radio technologies. In particular, we observe that the IEEE 802.15.4 Clear Channel Assessment (CCA) mechanism does not reliably detect interfering LoRa transmissions. We therefore propose an enhanced CCA mechanism based on a Multi-Layer Perceptron classifier and show that it significantly reduces the number of unsuccessful transmissions, while remaining compatible with the IEEE 802.15.4 standard.

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Demo: Integration of a Platform for Energy Storage Experiments into a Generic Testbed Framework

October 2018

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16 Reads

Robert Hartung

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Jan Käberich

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[...]

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Per Gunningberg

Testbeds have become a common method to test systems under real conditions. However, testbeds are often specialised and designed for a specific purpose. We have developed a generic software framework to help building and extending testbeds. This demo shows how our newly developed platform for experimenting with energy storage devices is integrated into our software framework. We will demonstrate how our platform works and how it is used in our testbed.


A Platform for Experiments with Energy Storage Devices for Low-power Wireless Networks

October 2018

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28 Reads

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4 Citations

We present a hardware platform for performing experimental studies of energy storage devices for low power wireless networks. It is based on a low-cost custom card that can apply fine-grain synthetic loads ? both charge and discharge ? to a set of batteries or capacitors and measure their response in detail. Loads can be defined from a "live" trace of a running wireless device, from a recorded trace, or programmatically via a script. This approach makes it practical to run well controlled, large scale, long running experiments and to obtain high precision and accuracy. We describe two proof-of-concept experiments using rechargeable Li coin cells and capacitors to demonstrate the capabilities of our platform.




Investigating interference between LoRa and IEEE 802.15.4g networks

October 2017

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2,091 Reads

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79 Citations

The rapid growth of new radio technologies for Smart City/Building/Home applications means that models of cross-technology interference are needed to inform the development of higher layer protocols and applications. We systematically investigate interference interactions between LoRa and IEEE 802.15.4g networks. Our results show that LoRa can obtain high packet reception rates, even in presence of strong IEEE 802.15.4g interference. IEEE 802.15.4g is also shown to have some resilience to LoRa interference. Both effects are highly dependent on the LoRa radio's spreading factor and bandwidth configuration, as well as on the channelization. The results are shown to arise from the interaction between the two radios' modulation schemes. The data have implications for the design and analysis of protocols for both radio technologies.


Poster: Measuring PHY layer interactions between LoRa and IEEE 802.15.4g networks

June 2017

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286 Reads

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1 Citation

Advances in low pwer wireless communication have resulted in new radio technologies that can achieve long distance communication in energy efficient ways. An emerging problem in this scenario is interference between networks that share the same medium. The fact that these networks have a long transmission range increases the possibility of interference even more. Thus the investigation of how different networks can share the medium independently in a optimal way becomes an essential requirement for the IoT vision. In this poster, we present the first step of this investigation, which is measuring how LoRa and IEEE 802.15.4g PHY layers interfere.



Citations (31)


... The network server organizes MAC schedules centrally, while end devices operate in one of three modes: class A (intended for batterypowered devices) is purely producer-driven, best-effort with very limited support for downlink communication; class C is not suitable for the low-power domain; and class B as a tradeoff between both. LoRaWAN networks are subject to collisions [16,47] and scalability issues [14,17]. Class B, albeit rarely deployed, is designed to allow periodic downlink communication at low energy, and exhibits reliability issues [41,50,57]. ...

Reference:

Delay-Tolerant ICN and Its Application to LoRa
Cross-Technology Clear Channel Assessment for Low-Power Wide Area Networks
  • Citing Conference Paper
  • November 2019

... One example for the traditional datasheet approach is presented in [43]. Such approaches are analytical and, thus, allow for estimations without any measurements but are most likely too optimistic with respect to the lifetime, as, e.g., ref. [44] shows. Models based on empirical data are, therefore, preferred and also very common, e.g., [45][46][47]. ...

Towards realistic lifetime estimation in battery-powered IoT devices
  • Citing Conference Paper
  • November 2017

... Experimentally determined the amount of electromagnetic interference needed for blocking a channel in LoRa. Cross-technology interference between LoRa and IEEE 802.15.4g was experimentally evaluated by the authors of [91]. LoRa is typically more resistant to interference than IEEE 802.15.4g, with the radio settings (SF and BW) being critical to the level of tolerance. ...

Investigating interference between LoRa and IEEE 802.15.4g networks

... This scheme contains two algorithms: the preliminary coloring algorithm and the multicoloring algorithm. In [34] provides information based on simulations of homogenous beaconenabled IEEE 802.15.4 network using contention-based slotted CSMA and contention-free GTS allocations. The results highlight the interfering networks that interact with each other. ...

Modes of inter-network interaction in beacon-enabled IEEE 802.15.4 networks
  • Citing Conference Paper
  • June 2015

... Recent results suggst that protocol-level and networkscale interactions can have a significant effect on IoT performance. Interfering IEEE 802.15.4 PANs [3,5,7] and 6TiSCH+RPL [9] networks are seen to suffer intermittent episodes of severe disruption, even when the channel is only lightly loaded. This includes behaviors such as rapid oscillations in throughput and extend communication blackouts. ...

Reliability in co-located 802.15.4 personal area networks
  • Citing Conference Paper
  • July 2016

... In the literature, many models of batteries can be found; various approaches were used to model the properties of the battery varying from electrochemical very detailed models to the high level stochastic models. We found: electrochemical models, circuitelectric models, analytical models, Kinetic models, Stochastic models [5] [6] [7] [8] , modeling by fuzzy logic [9], The Kalman filter [10], and the artificial neurological network [11]. ...

Evaluating Battery Models in Wireless Sensor Networks
  • Citing Conference Paper
  • June 2013

Lecture Notes in Computer Science

... On the one hand, the sensor device should be operating continuously and sampling data frequently. On the other hand, even if temperature conditions are perfect, enabling the sensor(s) for frequent data sampling results in increasing the internal resistance of the battery and affecting its chemical and physical properties [97]. Operating the battery under such timing and intensity conditions will not enable it to provide voltage at a sufficient level that operates the connected device correctly, even with a considerable amount of unused charge being left. ...

How do the dynamics of battery discharge affect sensor lifetime?
  • Citing Conference Paper
  • April 2014