Sub-Noise Floor Channel Tracking
Cellular standards and networks have traditionally been optimized for the high throughput requirements of modern smartphones. Recently the Internet of Things (IoT) has emerged as a new application with vastly different requirements. Ericsson predicts, that there will be 15 billion smart devices with Internet connectivity. Potential applications include smart metering, tracking in logistics, environmental sensing, and smart buildings. Two new variants of LTE have been standardized as part of Release 13 in 2016  for this kind of device: LTE Cat-M1 (eMTC) and NB-IoT. They both offer reduced cost and power consumption, as well as improved coverage, but Cat-M1 supports more features and has a higher maximum throughput. As part of our communication platform, we are currently developing a modem, which supports both standards, at IIS.
With the improved coverage of these new LTE variants, channel estimation has become much more challenging. With blind physical layer repetitions, the performance of the channel estimation eventually limits the achievable coverage. In LTE reference symbols in each subframe are used to estimate the channel for the same subframe. Improvements have been proposed by combining the information from multiple consecutive subframes. However, any time and frequency offset will cause the channel to change over frequency and time.
During this project, your task is studying algorithms in order to improve the quality of the channel estimation for LTE Cat-M1 by accumulating information from multiple subframes. This should also work, with a residual frequency or time offset. You will also investigate the possibility of tracking the frequency and time offsets using the changes in the channel estimate. To do this, you will use and extend our existing Matlab LTE simulation framework. A hardware or software implementation for an RF SoC is also an option.
- Looking for 1-2 Semester/Master students
- Contact: Stefan Lippuner
- An interest in wireless communication and signal processing
- Matlab experience is an advantage
- 60% Theory, Algorithms and Simulation
- 20% Hardware/Software Co-Design (C, HLS/VHDL)
- 20% FPGA Verification
 3GPP. Release 13. http://www.3gpp.org/release-13, 2016.
 Dahlman, Erik, Stefan Parkvall, and Johan Skold. "4G, LTE-advanced Pro and the Road to 5G". Academic Press, 2016.