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In 2000, the Signal Processing and Speech Communication Laboratory (SPSC Lab) of Graz University of Technology (TU Graz) was founded as a research and education center in nonlinear signal processing and computational intelligence, algorithm engineering, as well as circuits & systems modeling and design. It covers applications in wireless communications, speech/audio communication, and telecommunications.
If you want to learn more about Signal Processing, click: What is Signal Processing?
The Research of SPSC Lab addresses fundamental and applied research problems in five scientific areas:
Result of the Month
Direct Multipath-Based SLAM [link]
In future wireless networks, the availability of information on the position of mobile agents and the propagation environment can enable new services and increase the throughput and robustness of communications. Multipath-based simultaneous localization and mapping (SLAM) aims at estimating the position of agents and reflecting features in the environment by exploiting the relationship between the local geometry and multipath components (MPCs) in received radio signals. Existing multipath-based SLAM methods preprocess received radio signals using a channel estimator. The channel estimator lowers the data rate by extracting a set of dispersion parameters for each MPC. These parameters are then used as measurements for SLAM. Bayesian estimation for multipath-based SLAM is facilitated by the lower data rate. However, due to finite resolution capabilities limited by signal bandwidth, channel estimation is prone to errors and MPC parameters may be extracted incorrectly and lead to a reduced SLAM performance. We propose a multipath-based SLAM approach that directly uses received radio signals as inputs. A new statistical model that can effectively be represented by a factor graph is introduced. The factor graph is the starting point for the development of an efficient belief propagation (BP) method for multipath-based SLAM that avoids data preprocessing by a channel estimator. Numerical results based on synthetic and real data in challenging single-input, single-output (SISO) scenarios demonstrate that the proposed method outperforms conventional methods in terms of localization and mapping accuracy.
The Figure shows a flow diagram of the proposed Direct-SLAM compared to conventional multipath-based SLAM and the factor graph representing the statistical model of Direct-SLAM.
The preprint of the paper can be found here.
Contact: Erik LeitingerLatest News
17 Jul 2024 Research and Teaching Associate (Pre-Doc) in Signal Processing and Speech Communication
04 Jun 2024 Menschliche Gespräche mit einem Roboterkopf
08 Sep 2023 Research and Teaching Associate in Signal Processing and Speech Communicartion (Two PhD position)
06 Oct 2022 Student Projects Information Event: 14.10., 15:00 (BSc SP; MSc Project and Master Theses)
22 Mar 2022 Two PhD Positions in Wireless Communications and Positioning
03 Mar 2022 Press release on AI based denoising filters
03 Mar 2022 Christian Knoll received the Josef Krainer Award for his PhD Thesis
20 Apr 2021 Press release covering the H2020 project REINDEER has been published
01 Mar 2021 Course "Array Signal Processing" starting end of May 2021
01 Jan 2021 H2020 project REINDEER has been started
Check older news here.