Ultra Dense Indoor MaMIMO CSI Dataset
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- Sibren De Bast
- Last updated:
- Tue, 05/17/2022 - 22:21
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This dataset contains thousands of Channel State Information (CSI) samples collected using the 64-antenna KU Leuven Massive MIMO testbed. The measurements focused on four different antenna array topologies; URA LoS, URA NLoS, ULA LoS and, DIS LoS. The users channel is collected using CNC-tables, resulting in a dataset where all samples are provided with a very accurate spatial label. The user position is sweeped across a 9 squared meter area, halting every 5 millimeter, resulting in a dataset size of 252,004 samples for each measured topology. To the best of our knowledge, this is the biggest open dataset containing measured MaMIMO CSI samples. The dataset can, for example, be used to visualise precoders and validate positioning algorithms.
The dataset contains Channel State Information (CSI) samples, recorded with the KU Leuven Massive MIMO testbed. This was done for many user positions laying on a grid. The Base Station (BS) is equipped with 64 antennas, each receiving a predefined pilot signal from each position. Using these pilot signals, the CSI is estimated for 100 subcarriers, evenly spaced in frequency over a 20 MHz bandwidth. As a result, the complex numbered matrix H represents the measured CSI for one location. This matrix spans N rows and K columns, with N being the number of BS antennas and K the number of subcarriers. For further details about the system, the National Instruments Massive MIMO Application Framework documentation can be consulted.
To collect the CSI from many different user locations, four single-antenna User Equipments were positioned in an office. Their antennas were moved along a predefined route using CNC XY-tables. This route zigzagged along a grid taking steps of 5 mm. The total grid spans 1.25 m by 1.25 m. By using these XY-tables the error on the positional label is less than 1 mm, which results in a very accurate dataset. This resulted in a dataset containing 252004 CSI samples spatially labelled with an accuracy of less than 1 mm.
Furthermore, the testbed’s BS is designed to be very flexible in the deployment of the antenna array. This allowed for the creation of three different datasets, each with a unique antenna deployment. First, a Uniform Rectangular Array (URA) of 8 by 8 antennas was deployed, both in LoS and NLoS, using a metal blocker. Second, Uniform Linear Array (ULA) of 64 antennas on one line was deployed. Finally, the antennas were distributed over the room in pairs of eight, making up the distributed (DIS) scenario.
The different deployments can be seen in the picture in attachment. In all cases, the antennas are placed 1 m from the XY-tables. The yellow rectangles on the figure depict the 1.25 m by 1.25 m areas where the XY-tables are able to move the users in. The spacing in between the XY-tables is dictated by the space needed for the motors powering the movements and the cables connecting them to the controllers. These tables were synchronised over Ethernet with the BS to ensure the sampled H has a correct spatial label, enabling a highly accurate dataset.
During the measurements, the BS was configured to use a centre frequency of 2.61 GHz, giving a wavelength λ of 114.56 mm. The system used a bandwidth of 20 MHz. The origin of the space was defined as the middle of the URA. From this point in space, the x- and y-positions of the users and antennas were measured. These locations are provided in 3D in the dataset.
- ultradense_dataset ultra_dense.zip (17.04 GB)
- nomadic_dataset.zip (474.67 MB)
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