Optimizing a dynamic Network of Ranging Devices (HWSW Group)

With the increased usage of the UWB technology for ranging devices, the use cases for such systems become ever more complex. One of the challenges future localization system will face is the management of highly dynamic networks of multiple devices, which need to be localized in a very short time frame. Such networks are usually characterized by the high turnover of participating devices, dynamically joining and leaving the network. Addressing this problem, the ISO/IEEE consortium is currently working on a standard, which shall allow the setup of a so-called contention free phase, in which each device is assigned a timeslot, in which it can range with a central reader. This central reader manages the network. A system model, simulating the devices and their network is currently implemented by the HWSW Group. This framework shall in future be used to allow optimizations of the networking protocol, finding optimal timeslot allocations for arbitrary numbers of ranging devices.


Download as PDF

Student Target Groups:

  • Master students in ICE, Computer Engineering ,or SD-BM

Thesis Type:

  • Seminar (Master) Project
  • Master Thesis

Goal:

The goal of this project is to find a method, allowing to optimize the timeslot allocation for an arbitrary number of ranging devices, dynamically entering and leaving the network. Depending on the use case, two parameters shall be optimized. The power consumption of each device, and the maximum range measurements per device, in a predefined time frame. As these parameters oppose each other, a feasible compromise between them shall be found. Further limiting requirements must also be considered (e.g. minimum ranging cycles per device, etc.). For these optimizations, various algorithms are to be implemented and their results must be compared to each other and interpreted.


Tasks:

  • Familiarize with existing work / tools / framework – find suitable algorithms.
  • Design and implement the optimization framework.
  • Implement found algorithms – compare and interpret their solutions.
  • Summarize your findings in a written report.

     

        Recommended Prior Knowledge:

        • Interest in network problems, C++ (SystemC), optimization problems, algorithms

          Start:

          • a.s.a.p.

          Contact: