4 citations · 5 across the 8 of their papers we have counts for
7 papers · 1 filter
3D Cooperative User Tracking for Distributed Integrated Sensing and Communication
Yingjie Xu, Xuesong Cai, Michiel Sandra +2
As integrated sensing and communication (ISAC) becomes an integral part of 6G networks, distributed ISAC (DISAC) is expected to enhance both sensing and communication performance t…
Interacting Object-Enabled Clustering and Characterization of Distributed MIMO Channels
Yingjie Xu, Michiel Sandra, Xuesong Cai +2
Distributed multiple-input multiple-output (MIMO), also known as cell-free massive MIMO, emerges as a promising technology for sixth-generation (6G) systems to support uniform cove…
Spatial separation of closely-spaced users in measured distributed massive MIMO channels
Yingjie Xu, Michiel Sandra, Xuesong Cai +2
Aiming for the sixth generation (6G) wireless communications, distributed massive multiple-input multiple-output (MIMO) systems hold significant potential for spatial multiplexing.…
A Wideband Distributed Massive MIMO Channel Sounder for Communication and Sensing
Michiel Sandra, Christian Nelson, Xuhong Li +3
Channel sounding is a vital step in understanding wireless channels for the design and deployment of wireless communication systems. In this paper, we present the design and implem…
An Open Dataset Storage Standard for 6G Testbeds
Gilles Callebaut, Michiel Sandra, Christian Nelson +7
The emergence of sixth-generation (6G) networks has spurred the development of novel testbeds, including sub-THz networks, cell-free systems, and 6G simulators. To maximize the ben…
High-Precision Machine-Learning Based Indoor Localization with Massive MIMO System
Guoda Tian, Ilayda Yaman, Michiel Sandra +3
High-precision cellular-based localization is one of the key technologies for next-generation communication systems. In this paper, we investigate the potential of applying machine…
The LuViRA Dataset: Synchronized Vision, Radio, and Audio Sensors for Indoor Localization
Ilayda Yaman, Guoda Tian, Martin Larsson +11
We present a synchronized multisensory dataset for accurate and robust indoor localization: the Lund University Vision, Radio, and Audio (LuViRA) Dataset. The dataset includes colo…