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12 results for “MIMO”
Measurement-based MIMO channel model at 140GHz
<p><strong>1. Introduction</strong></p> <p>The file “gen_dd_channel.zip” is a package of a wideband multiple-input multiple-output (MIMO) stored radio channel model at 140 GHz in indoor hall, outdoor suburban, residential and urban scenarios. The package consists of 1) measured wideband double-directional multipath data sets estimated from radio channel sounding and processed through measurement-based ray-launching and 2) MATLAB code sets that allows users to generate wideband MIMO radio channels with various antenna array types, e.g., uniform planar and circular arrays at link ends.</p> <p><strong>2. What does this package do?</strong></p> <p><em>Outputs of the channel model</em></p> <p>The MATLAB file “ChannelGeneratorDD_hexax.m” gives the following variables, among others. The .m file also gives optional figures illustrating antennas and radio channel responses.</p> <table> <tbody> <tr> <td> <p>Variables</p> </td> <td> <p>Descriptions</p> </td> </tr> <tr> <td> <p><em>CIR</em></p> </td> <td> <p>MIMO channel impulse responses</p> </td> </tr> <tr> <td> <p><em>CFR</em></p> </td> <td> <p>MIMO channel frequency responses</p> </td> </tr> </tbody> </table> <p><em>Inputs to the channel model</em></p> <p>In order for the MATLAB file “ChannelGeneratorDD_hexax.m” to run properly, the following inputs are required.</p> <table> <tbody> <tr> <td> <p>Directory</p> </td> <td> <p>Descriptions</p> </td> </tr> <tr> <td> <p>data_030123_double_directional_paths</p> </td> <td> <p>Double-directional multipath data, measured and complemented by ray-launching tool, for various cellular sites.</p> </td> </tr> </tbody> </table> <p><em>User’s parameters</em></p> <p>When using “ChannelGeneratorDD_hexax.m”, the following choices are available.</p> <table> <tbody> <tr> <td> <p>Features</p> </td> <td> <p>Choices</p> </td> </tr> <tr> <td> <p>Channel model types for transfer function generation</p> </td> <td> <ul> <li> <p>'<em>snapshot</em>': single time sample per link = static, random phase for each path, amplitude from measurements</p> </li> <li>'<em>virtualMotion</em>': Doppler shifts & temporal fading, static propagation parameters, random phase for each path, amplitude from measurements, Doppler frequency per path from AoA and velocity vector</li> </ul> </td> </tr> <tr> <td> <p>Antenna / beam shapes</p> </td> <td> <ul> <li> <p>'<em>single3GPP</em>': single antenna element with power pattern shape defined in 3GPP, adjustable HPBW etc.</p> </li> <li> <p>'<em>URA</em>': uniform rectangular array, omni-directional elements</p> </li> <li>'<em>UCA</em>': uniform circular array, omni-directional elements</li> </ul> </td> </tr> </tbody> </table> <p><strong>List of files in the dataset</strong></p> <p><em>MATLAB codes that implement the channel model</em></p> <p>The MATLAB files consist of the following files.</p> <table> <tbody> <tr> <td> <p>File and directory names</p> </td> <td> <p>Descriptions</p> </td> </tr> <tr> <td> <p>readme_100223.txt</p> </td> <td> <p>Readme file; please read it before using the files</p> </td> </tr> <tr> <td> <p>ChannelGeneratorDD_hexax.m</p> </td> <td> <p>Main code to run; a code to integrate antenna arrays and double-directional path data to derive MIMO radio channels. No need to see/edit other files.</p> </td> </tr> <tr> <td> <p>gen_pathDD.m, randl.m, randLoc.m</p> </td> <td> <p>Sub-routines used in ChannelGeneratorDD_hexax.m; no need of modifications.</p> </td> </tr> <tr> <td> <p>Hexa-X channel generator DD_presentation.pdf</p> </td> <td> <p>User manual of ChannelGeneratorDD_hexax.m.</p> </td> </tr> </tbody> </table> <p> </p> <p><em>Measured multipath data</em></p> <p>The directory "data_030123_double_directional_paths" in the package contains the following files.</p> <table> <tbody> <tr> <td> <p>Filenames</p> </td> <td> <p>Descriptions</p> </td> </tr> <tr> <td> <p>readme_100223.txt</p> </td> <td> <p>Readme file; please read it before using the files</p> </td> </tr> <tr> <td> <p>RTdata_[<em>scenario</em>]_[<em>date</em>].mat</p> </td> <td> <p>Containing double-directional multipath parameters at 140 GHz in the specified scenario, estimated from radio channel sounding and ray-tracing.</p> </td> </tr> <tr> <td> <p>description_of_data_dd_[<em>scenario</em>].pdf</p> </td> <td> <p>Explaining data formats, the measurement site and sample results.</p> </td> </tr> </tbody> </table> <p><strong>References</strong></p> <p>Details of the data set are available in the following two documents:</p> <p><em>The stored channel models</em></p> <p>A. Nimr (ed.), "Hexa-X Deliverable D2.3 Radio models and enabling techniques towards ultra-high data rate links and capacity in 6G," April 2023, available: https://hexa-x.eu/deliverables/</p> <p>@misc{Hexa-XD23,<br> author = {{A. Nimr (ed.)}},<br> title = {{Hexa-X Deliverable D2.3 Radio models and enabling techniques towards ultra-high data rate links and capacity in 6G}},<br> year = {2023},<br> month = {Apr.},<br> howpublished = {https://hexa-x.eu/deliverables/},<br>}</p> <p><em>Derivation of the data, i.e., radio channel sounding and measurement-based ray-launching</em></p> <p>M. F. De Guzman and K. Haneda, "Analysis of wave-interacting objects in indoor and outdoor environments at 142 GHz," IEEE Transactions on Antennas and Propagation, vol. 71, no. 12, pp. 9838-9848, Dec. 2023, doi: 10.1109/TAP.2023.3318861</p> <p>@ARTICLE{DeGuzman23_TAP,<br> author={De Guzman, Mar Francis and Haneda, Katsuyuki},<br> journal={IEEE Transactions on Antennas and Propagation}, <br> title={Analysis of Wave-Interacting Objects in Indoor and Outdoor Environments at 142 {GHz}}, <br> year={2023},<br> volume={71},<br> number={12},<br> pages={9838-9848},<br>}</p> <p>Finally, the code “randl.m” are from the following MATLAB Central File Exchange.</p> <p>Hristo Zhivomirov (2023). Generation of Random Numbers with Laplace Distribution (https://www.mathworks.com/matlabcentral/fileexchange/53397-generation-of-random-numbers-with-laplace-distribution), MATLAB Central File Exchange. Retrieved February 15, 2023.</p> <p><strong>Data usage terms</strong></p> <p>Any usage of the data must be upon consent on the following conditions:</p> <ul> <li>The file “ChannelGeneratorDD_hexax.m” is owned by OUL. Contact: Dr. Pekka Kyösti, Pekka.Kyosti@oulu.fi.</li> <li>The other files and those in the directories, except for “randl.m”, are owned by AAU. Contact: Mr. Mar Francis de Guzman, francis.deguzman@aalto.fi.</li> <li>When a scientific paper is published that exploits the data and code, please cite this data set; the citation can be downloaded from the zenodo page of this data set.</li> </ul>
Beam Alignment Measurements using a Hybrid Massive MIMO Testbed
<p>Measurement data and processing code for Mathworks Matlab underlying the beam alignment results of the publication. The results compare 3 algorithms for beam alignment and are measured at 2.4GHz using the Hybrid Massive MIMO testbed of the CommIT chair of the Technische Universität Berlin.</p> <p>Type of Data: Processed data (Measurement results and processing code)</p> <p>Hardware/software used: Technische Universität Berlin CommIT Hybrid Massive MIMO testbed, Mathworks Matlab</p> <p>Data format: Measurements: Matlab mat data files, Code: m UTF8 text files</p> <p>Source: experiments</p> <p>Number of samples: 2 locations</p> <p>Size per sample: 10 files per location</p> <p>Total size of samples: 170MB</p>
Antijamming Schemes for Generalized MIMO Y Channel
<p>The following dataset contains the Block Error Rate (BLER) results from the link-level simulator, obtained for the proposed anti-jamming schemes (AJ-SSA, JIC), which were compared to those of the iterative beamforming optimization algorithm (labeled as SSA and SSA no jammer, when the jammer is absent). Simulations were conducted for two antenna configurations: 4x4 and 8x8.</p>
Comparison Results for Global Optimization Solvers Using a MIMO System With Two, Three and Four Active Layers as a Benchmark
<p>Benchmark data for GPU-based interval optimization of a simulated MIMO system with two, three and four active layers. We compare popular optimization tools from C-XSC and GNU Octave to purely brute-force based techniques for the GPU. Execution times were measured in seconds.</p>
MmWave 28 GHz MIMO channel sounding data collected in a conference room
<p>Channel sounding data sampled using a 28 GHz switched array MIMO channel sounder in a conference room.</p> <p>More information can be found in <a href="https://arxiv.org/abs/2404.19297">the corresponding publication</a> (DOI: 10.1109/TCOMM.2024.3392805), while the underlying data employs a self-explanatory structure, implemented in Matlab.</p>
Plane-wave propagation path data from wideband MIMO channel sounding in an urban microcellular scenario
<p>We provide plane-wave propagation path data from a wideband MIMO radio channel sounding measurement in an urban microcell scenario. The binary Matlab file includes: direction of departure (DOD: variables "par.PhiTx" and "par.ThetaTx" in [rad]), direction of arrival (DOA: "par.PhiRx" and "par.ThetaRx" in [rad]), delay ("par.Tau" to be multiplied with 8.3ns, the tab length), and complex polarimetric path gain ("par.Alpha" is a 2x2 matrix, where element [1,1]=TXtheta ->RXtheta, [1,2]=TXphi ->RXtheta, [2,1]=TXtheta->RXphi, and [2,2]=TXphi->RXphi), for the 30 strongest signal paths (from TX to RX) at each of the 4574 RX locations along the route described below. In the element names above, the term "theta" refers to the vertically polarised component, and accordingly the term "phi" referes to the horizontally polarised component.<br> Note #1: The exact RX location for each individual measured radio channel was NOT recorded (see route description below). <br> Note #2: The complex path gain (par.Alpha) is NOT calibrated, but depends on the initially fixed AGC level in the receiver, which was chosen to provide the best dynamic range for the given mobile (RX) route.<br> Both these limitations are seen reasonable since this dataset is meant for the realistic *statistical comparison* of the performance of different RX antennas in a microcell environment (and not to determine the actual received power at each exact location of the measured route).<br> Background information: The provided dataset is processed and is based on a radio channel sounder measurement at 5.3 GHz, carried out in downtown Helsinki, Finland, in April 2004. The uniform rectangular transmit (TX) array was placed at 10 m height in Aleksanterinkatu-street (an approx. 15-m wide street canyon), in front of the Nordea building, broadside pointing westwards (towards Stockmann building). The semishperical receive (RX) array was moved at 1.6-m height and for about 50 m along Aleksanterinkatu-street in line-of-sight (LOS), i.e. from in front of Kluuvi shopping centre westwards just across the crossing of Kluuvikatu-street. The TX and RX arrays cover the relevant azimuth and elevation ranges, so that this plane wave propagation path data can directly be combined with the polarimetric directional radiation pattern(s) of an antenna (array).</p>
A Survey of Five Generations of MIMO Multiband Base Station Antennas
<p>This article presents an overview of the challenges faced by base station antennas over time and their general solutions. Techniques are discussed which have been developed over the time to overcome design challenges of 5G base station antennas.</p>
5G-PICTURE WP6 Stadium Massive MIMO Demo Results
<p>This data set comprises of the Massive MIMO demo results and KPIs, as demonstrated in real-time on 13 March 2020, as part of the 5G-PICTURE WP6 Stadium Demo.</p>
MIdazolam Versus MOrphine in Acute Pulmonary Edema (MIMO Trial)
ClinicalTrials.gov study NCT02856698. IPD Sharing: NO. Countries: 1. Publications: 0.
Dataset for Power Control in Cell-Free Massive MIMO
<h2><strong>Description</strong></h2> <p>This repository contains a dataset that represents the simulation of 12 distinct cell-free massive MIMO scenarios. Each scenario includes 20,000 setups, derived from a customized version of the MATLAB code package available <a href="https://github.com/emilbjornson/cell-free-book.git" target="_blank" rel="noopener">here</a>. The simulations take into account three power control optimization schemes: max-min Spectral Efficiency (SE) fairness, sum SE maximization, and Fractional Power Control (FPC).</p> <p>The results for the simulation for each scenario are split across 20 MATLAB storage files ('power_control_part#.mat'), with each file encompassing 1,000 setups. Denoting the number of access points (APs) as L, the numer of user equipments (UEs ) as K, and the number of setups as M. The variables within these files are defined as follows:</p> <ul> <li>'gainOverNoise': This is a [L x K x M] matrix that contains the large-scale fading coefficients.</li> <li>'pk_UL_nopt_LPMMSE_<strong>X</strong>': This is a [K x M] matrix that includes the power coefficients with; (1) <strong>X</strong> = 'maxmin' for the max-min SE fairness, (2) <strong>X</strong> = 'sumSE' for the sum SE maximization, and (3) <strong>X</strong> = 'FPC' for the FPC power scheme.</li> <li>'SE_UL_nopt_LPMMSE_<strong>X</strong>': This is a [K x M] matrix that includes the SE per UE with; (1) <strong>X</strong> = 'full' for all the UEs transmitting with maximum power, (2) <strong>X</strong> = 'maxmin' for the max-min SE fairness, (3) <strong>X</strong> = 'sumSE' for the sum SE maximization, and (4) <strong>X</strong> = 'FPC' for the FPC power scheme.</li> <li>'bk_dist_<strong>X</strong>': This is a [K x M] matrix that represents the average channel gain of the desired signal with; (1) <strong>X</strong> = 'frac' for the FPC, and (2) <strong>X</strong> = 'full' for the rest of power control schemes.</li> <li>'ck_dist_<strong>X</strong>': This is a [K x K x M] matrix the represents the average channel gains for the respective interfering signals; (1) <strong>X</strong> = 'frac' for the FPC, and (2) <strong>X</strong> = 'full' for the rest of power control schemes.</li> <li>'sigma2_dist_XX': This is a [K x M] matrix the represents the effective noise variance; (1) <strong>X</strong> = 'frac' for the FPC, and (2) <strong>X</strong> = 'full' for the rest of power control schemes.</li> </ul> <p>Additonally, the file 'setup.mat' contains information about the simulated environment.</p> <p>Please refer to the conference paper above for more detailed information about the simulations.</p> <p>The simulation code is available <a href="https://github.com/Fivecomm/cell-free-power-control-DNN.git" target="_blank" rel="noopener">here</a> on GitHub for training and testing the DNN models.</p> <h2><strong>Referencing</strong></h2> <p>If you in any way use this dataset for research that results in publications, please cite our original article listed above.</p> <p>G. García-Barrios, M. Fuentes, and D. Martín-Sacristán, “A Flexible Low-Complexity DNN Solution for Power Control in Cell-Free Massive MIMO,” in 2024 IEEE 35th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2024, pp. 1–6.</p> <h2><strong>Acknowledgements</strong></h2> <p>This work is supported by the grant from the Spanish ministry of economic affairs and digital transformation and of the European Union – NextGenerationEU [UNICO-5G I+D/AROMA3D-Earth] (TSI-063000-2021-69).</p>
Open Label Tolerability Study of ISOThrive Prebiotic Nectar (MIMO) in Subjects With Constipation
ClinicalTrials.gov study NCT04677634. IPD Sharing: NO. Countries: 1. Publications: 0.
Error Governor for Active Fault Tolerance in PID Control of MIMO Systems
<p>The dataset complements the article under review, "Error Governor for Active Fault Tolerance in PID Control of MIMO Systems," by reporting the simulation results obtained from testing the proposed Error Governor approach on the Zagi flying-wing UAV model.</p> <p>Run the main file "plot_images.m" to generate plots from the simulation data.</p>
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