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5 results for “5G NR”
Dataset for Radio-based Sensing and Indoor Mapping with Millimeter-Wave 5G NR Signals
<p>Dataset of paper "Radio-based Sensing and Indoor Mapping with Millimeter-Wave 5G NR Signals" presented in International Conference on Localization and GNSS (ICL-GNSS) 2020.</p> <p>The measurement data contains indoor mapping results using millimeter-wave 5G NR signals at 28 GHz. The measurement campaign was conducted at an indoor office environment in Hervanta Campus of Tampere University. Six different sets of measurements contain the range profiles after the proposed radar processing.</p> <p>The file "indoorMapping_processing.m" shows how to process and plot the shared data.</p> <p> </p> <p> </p>
DATASET: IQ SAMPLES OF LTE, 5G NR, WI-FI, ITS-G5, AND C-V2X PC5
<div> <div> <div> <h1>Dataset: IQ samples of LTE, 5G NR, WiFi, ITS-G5, and C-V2X PC5</h1> <p>The dataset comprises IQ samples captured from ITSG-5, C-V2X PC5, WiFi, LTE, 5G NR and Noise. In each dataset cluster, 7500 examples are collected from each considered technology. The dataset collected was used for technology recognition and traffic charchterization model. More details on the structure and performance of the model can be found <a href="https://www.sciencedirect.com/science/article/abs/pii/S2214209622001103">here</a>.</p> <p> </p> </div> </div> </div> <div> <div> <div> <h1>Description of Dataset Collection</h1> <h2>LTE</h2> <p>For LTE dataset collection, <a href="https://www.srslte.com/" target="_blank" rel="nofollow noopener">srsRAN</a>, an open-source SDR platform, is used. This LTE SDR implementation is used to collect samples for the LTE dataset. The indoor testbed setup used to collect our dataset consists of one eNB host PC and one UE host PC. Each host PC is connected to a USRP X310 board, which is used as the RF front end. We use the latest srsRAN version 21.04, which is installed on each host PC. For the LTE dataset collection, the FDD mode with a 10 MHz bandwidth and a 5.9 GHz center frequency is used for the down-link traffic. For the LTE dataset, the traffic load was varied between 5 and 50 Mbps, and the MCS used was varied by manually configuring from MCS index 1 to 28 .</p> <h2>5G NR</h2> <p>The <a href="https://openairinterface.org/" target="_blank" rel="nofollow noopener">OpenAirInterface</a> SDR solution is used for 5G NR dataset collection. OpenAirInterface is an open source SDR platform that provides a 3GPP compliant implementation of eNB, UE, and EPC. The OpenAirInterface SDR solution also includes a 5G non-stand alone (NSA) mode which supports 5G networks by using existing 4G infrastructure. This SDR-based 5G network setup is used to collect the IQ samples for the 5G NR dataset. For the 5G NR dataset collection, a 1:1 static TDD configuration is used for up-link and down-link traffic in NSA mode. Numerology 1 is used at 10 MHz bandwidth and center frequency of 5.9 GHz. For the 5G NR dataset, the MCS used was varied by manually configuring different values ranging from MCS index 1 to 28, and the traffic load was varied between 5 and 50 Mbps.</p> <h2>Wi-Fi</h2> <p>For the WiFi dataset collection, the <a href="https://github.com/open-sdr/openwifi" target="_blank" rel="nofollow noopener">openwifi</a> SDR solution is used. openwifi is an open-source full-stack IEEE 802.11 a/g/n SDR implementation based on the Xilinx Zynq System on Chip that includes a Field Programmable Gate Array (FPGA) and an ARM processor. For our dataset, we used an IEEE802.11n access point and a client connected to it. WiFi traffic generated cover a wide range of traffic loads, i.e., 10–200 packets per second (pps), with packet sizes ranging from 500 to 1500 bytes. The MCS used was varied by manually configuring the MCS index value between 0 and 7.</p> <h2>ITS-G5 and C-V2X PC5</h2> <p>The <a href="https://www.marquez-barja.com/images/papers/vehicuularcomms21-openaccess-version.pdf" target="_blank" rel="nofollow noopener">CAMINO</a> framework was used for the ITS-G5 and C-V2X PC5 dataset collection. CAMINO is a core framework for managing the V2X communication technologies, including ITS-G5, C-V2X PC5 and C-V2X Uu (5G/4G). The CAMINO framework is used to dynamically generate standardized C-ITS service packets, including Cooperative Awareness (CA), Decentralized Environmental Notification (DEN), and Infrastructure to Vehicle Information (IVI) message packets. The CAMINO software is implemented on the infrastructure deployed as part of the <a href="https://ieeexplore.ieee.org/document/9621229" target="_blank" rel="nofollow noopener">Belgian Smart Highway testbed</a>. The Smart Highway is a testbed deployed by IMEC on the E313 highway, near Antwerp, Flanders. The Smart Highway testbed consists of eight RSUs and 2 OBUs. Each RSU and OBU includes a general purpose CPU running the CAMINO software, and Cohda MK5 and MK6c modules, which are COTS ITS-G5 and C-V2X modules respectively. In our dataset collection, RSU4 is used as a transmitter, and a USRP N310 connected to RSU3 is used to capture and store the samples. To represent a wide range of traffic characteristics, different packet sizes of 300B for CA, 300B and 600B for DEN, and 600B for IVI packets were used at inter-packet intervals of 20, 50, 100, and 200 seconds. The MCS used were varied by manually changing the MCS index value in the configuration files of the Cohda devices. The MCS index of ITS-G5 varied from 0 to 7. For the C-V2X PC5, the MCS is varied between 0 and 20.</p> </div> </div> </div> <div> </div>
5G NR Full Grid Over-the-Air Measurements
<p>This data set is collected for the full resource grid over-the-air measurements of 5G NR downlink tranmission. Some different scenarios including different numerologies, center frequencies, bandwidths and fading are included. Please refer to the PDF file in the folder for the detailed description of the scenarios</p>
5G NR Full Grid Measurements
<p>This data set is collected for the full resource grid measurements of 5G NR downlink tranmission. Some different scenarios including different numerologies, center frequencies, bandwidths and fading are included. Please refer to the PDF file in the folder for the detailed description of the scenarios</p>
Experimental Evaluation of All-Optical Up- and Down-Conversion of 3GPP 5G NR Signals using an Optomechanical Crystal Cavity Frequency Comb
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