Frank Hessel, M.Sc.

  2023 Completed

Machine Learning Based Data Rate Optimization for Mobile LoRaWAN Sensors

Supervisor: Luis Alves Frank Hessel

Adaptive Data Rate is a feature of LoRaWAN that allows to optimize the network performance by adjusting the data rate of end devices based on their current channel conditions. Current approaches to ADR optimization algorithms focus on static or low-mobile end devices, and the specification recommends to disable ADR for mobile devices, e.g. location trackers. To let these devices also benefit from ADR adjustments, this thesis suggests to implement a predictive ADR algorithm based on deep reinforcement learning. The algorithm is evaluated on a real-world data set captured in the city of Darmstadt.

  2023 In progress

Automated Surveillance Recognition in Smart Environments

Supervisor: Matthias Gazzari Frank Hessel

This topic is about implementing various models to recognize the presence of as many smart things as possible based on sensor or other time series data. The goal of this topic is to compare and evaluate these models against each other in certain settings like in a smart home environment.

  2022 Completed

LoRaWAN in Disaster Scenarios

Supervisor: Frank Hessel

LoRa comes with characteristics beneficial in crisis situations, like its long range and the low power consumption, which allows to run running devices on batteries significantly longer than, e.g., cellular base stations. However, LoRaWAN does not benefit from these characteristics, as it depends on a centralized, cloud-based network server infrastructure. If gateways can no longer access the backing network, forwarding stops and the network fails in the affected region. This thesis investigates collaboration between gateways to transparently forward frames from LoRaWAN devices in regions suffering from an outage of the backing network.

  2022 In progress

Low-Power Network Support for the Recovery of Collapsed 6G Systems

Supervisor: Leon Würsching Frank Hessel

A resilient 6G network will be prepared for different failure scenarios and can absorb incidents to a certain level. However, there may be incidents that cannot be absorbed, e.g., a failure of the entire 6G core network due to a large-scale cyber attack. Further possible consequences of such an incident include a large-scale power outage affecting either parts or even the entire mobile network. In this type of scenario, the 6G network would collapse and split into smaller networks. Such a small network could, e.g., consist of a single isolated base station running on emergency power, and the users connected to it. From here, isolated basestations have to reconnect with other base stations to recover some functionality of the 6G network. However, the need to conserve energy further complicates the recovery process because base stations are running on emergency power. This thesis evaluates how such a recovery process of the 6G network can be supported with ad-hoc low-power networks. In this thesis, the student will explore how isolated base stations can coordinate the reconnection of isolated base stations via a low-power network. This includes discussing and choosing a suitable lower-layer protocol as a basis for the low-power network implementing a basic consensus protocol to make distributed decisions testing the developed protocol in simulation.

  2022 Completed

Updating Heterogeneous LoRaWAN Nodes Using A Modular LoRaWAN-Stack

Supervisor: Frank Hessel

The LoRaWAN 1.0 has been shown to suffer from security vulnerabilities which require updating the LoRaWAN implementation on respective sensor nodes. However, updating the firmware of LoRaWAN end devices is a demanding task, as data rate and duty cycle limit the throughput to only a few kilobytes per second. Heterogeneity amongst sensors exacerbates the situation by requiring dedicated images for each sensor type. The thesis addresses both problems by improving the updatability of LoRaWAN end devices by allowing to replace single functions of the LoRaWAN stack with architecture-independent drop-ins based on WebAssembly.

  2022 Completed

Practical Evaluation of LoRaWAN in IIoT Environments

Supervisor: Frank Hessel

  2022 Available now

Generalized Network Coded Cooperation in High Density LoRa-Networks

Supervisor: Luis Alves Frank Hessel

The wireless channel is a non-linear and time-varying system. Thus, it represents a harsh environment to conduct transfers of information. One of the variables that predict the outage performance of transmissions over the wireless channel is the diversity order, where systems with higher diversity order experience a lower outage probability at a specific signal-to-noise ratio (SNR). Diversity can be achieved through several means, with the most simple being repetitions (retransmissions) of the same information over different instances of the wireless medium, i.e. over another time period or frequency. One very relevant means is the use of multiple antennas, which adds diversity by also incorporating a spatial element. However, this element can also be obtained when devices with transmissions to a common destination aid each other with retransmitting their partner's information frames. That is the concept behind cooperative communication: achieving a spatial diversity gain without requiring multiple antennas on each device [1]. Network Coded Cooperation (NCC) is a more complex cooperative technique whereby devices perform linear combinations of the data contained in their own and their partner's information frame, creating a parity frame. This allows for an even higher diversity order gain without requiring any additional transmissions beyond the standard information and cooperative phases seen in cooperative communications [2]. This kind of technique can therefore be especially useful in scenarios where multiple devices share a common base station and require energy-efficient communications, such as in LoRa-based networks. LoRa is a prime modulation technique for enabling Low-Power Wide Area Networks (LPWANs), providing adequate interference prevention, relatively low power consumption, and long range. These benefits, however, do not scale well with increases in the network density [3]. Note that, in these high-density scenarios, increasing diversity by simply realizing more transmissions results in an increased collision probability, i.e. even higher interference. For LoRa-networks, this also means the network loses maximum range. Given that the number of connected devices is expected to balloon in this decade, LoRa-based protocols must be adapted to mitigate high levels of interference. It has been shown that using NCC can produce positive results in the high-density scenario LoRa-based network when associated with a fast inter-device transmission of information frames using high rate frequency shift-keying (FSK). However, previous analyses were purely theoretical and limited to evaluating a two-way cooperation process [3]. This thesis will tackle the empirical and theoretical challenges of implementing generalized network-coded cooperation on LoRa-based networks. Cooperation will be expanded to include multiple devices within the cooperation range, which will generate a higher diversity order for the uplink transmissions. The student is expected to be programing LoRa devices based on either the SX1272 or SX1276 transceivers to validate their results. If you have any interest in the described topic, please do not hesitate to get in touch. [1] Cooperative communication in wireless networks [2] Multiuser Cooperative Diversity Through Network Coding Based on Classical Coding Theory [3] Network-Coded Cooperative LoRa Network with D2D Communication