NYUSIM user Manual

this user manual). Time cluster - spatial lobe approach to cluster any measured or Ray traced data: The MATLAB code implementing the time cluster - spa-tial lobe (TCSL) algorithm used in the SSCM [3], [19]. User License: The user license for NYUSIM, which is also shown on the previous page of this user manual.This open-source license al NYUSIM Application Version 3.0. Last Modification 3/28/2021 - Update Notes. Version 3.0 introduces a MATLAB®-based indoor statistical channel model following the mathematical framework of the existing NYUSIM outdoor channel modeling approach, which can simulate indoor MIMO channel impulse responses from 500 MHz to 150 GHz with 0 Hz to 800. Changes to NYUSIM include: More operation steps were added on the top part of the simulator GUI to better instruct users. Detailed explanations of the half-power beamwidth (HPBW) and gain of the antenna array, and examples of how to create an antenna pattern given the HPBW and gain, were added in Section 2.1.1 of this user manual Version 1.3 Update Notes: Descriptions of the numbers of matrix columns and rows in the output .txt files containing the complex channel coefficients (H), phases (HPhases), and powers (HPowers) were corrected in Section 2.2.2 of this user manual

Compared to NYUSIM Version 1.5, there are several major new features added to Version 1.6 for line-of-sight (LOS) environments, angle-of-departure (AoD), angle-of-arrival (AoA), extended range option, and rural macrocell (RMa) modeling, which are detailed below. In the base code package of NYUSIM, a new MATLAB script with the name NYUSIM. (a) Fix 1: In Version 1.6 and earlier versions, NYUSIM only used the first TX antenna element with all RX antenna elements to generate the MIMO channel impulse responses, where NYUSIM should have used all TX antenna elements (N TX) with all RX antenna elements (N RX) when producing the MIMO channel impulse responses. In other words, earlier versions of NYUSIM only generated 1 x N RX complex. NYUSIM User Manual, New York, NY: New York University. Google Scholar; Martin, L. 2017. Conception d'une antenne compacte de station de base pour réseaux cellulaires. Doctoral Thesis. University of Nantes. Google Scholar; Meifang, Z. 2014. Geometry-based radio channel characterization and modeling: parameterization, implementation and validation

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versitat Wein (TUW) [1], NYUSIM of New York University Their user manual contains a list of implemented functions. Users can download and use the MATLAB code directly, and must have. At Roboteq, our passion is to develop products and technologies that allow large volume OEMs and enthusiasts alike to build innovative motion systems for automation, robotic and electrical transportation application RF Optimization Tutorial and Information for 2G,3G,4G and 5

NYUSIM Download Version 3

  1. Fix 2: In Version 1.6, a bug occurs when the RF bandwidth is set to be less than 800 MHz. The time resolution of the system becomes more coarse as the bandwidth is set by the user to be narrower than 800 MHz. Thus, fewer multipath components can be resolved at narrower bandwidth compared to the 800 MHz bandwidth
  2. The prediction models used in this study include the SUI, ABG, CI, and NYUSIM simulators using working frequencies of 3.5 GHz and 28 GHz with a bandwidth of 100 MHz and 800 MHz. The test results show that the NYUSIM simulator provides a path loss prediction value that is closest to the average path loss value with a margin value of 1.25 dB for.
  3. istic RadIo channel GenerAtor, is used for generating realistic radio channel impulse responses for system-level simulations of mobile radio networks. These simulations are used to deter
  4. The following is a partial list of tools written for Bio-SPICE, with links to the authoring institution, where available. Tools are available from a variety of locations. In addition to the links below, some tools are available when using the Bio-SPICE Dashboard's Update Center wizard. (See the user manual for more information.
  5. Feko® is used globally across multiple industries including aerospace, defense, automotive, communications, and consumer electronics to reduce the time-to-market. Feko addresses the broadest set of high-frequency electromagnetics applications, allowing teams to optimize wireless connectivity, including 5G, ensure electromagnetic compatibility (EMC), and perform radar cross section (RCS) and.

Massive multi-user (MU) multiple-input multiple-output (MIMO) and millimeter-Wave (mmWave) as well as terahertz (THz) communication are key technologies for 5G and future wireless systems [2, 3].Since wave propagation at mmWave and THz carrier frequencies is highly directional and experiences a strong path loss, only a small number of dominant transmission paths between each user equipment (UE. 3.1. Propagation Deterministic Mechanism. Real-world multipath/multiscatter propagation scenarios for three typical 5G use cases are depicted as in Figure 1: high-speed train (HST), vehicle-to-vehicle (V2V) in an urban environment, and crossroad (V2Vcrossroad) scenarios.First, case (a) comprises transmission from a fixed base station transmitter to a fast moving receiver in the presence of. Considering that networks based on New Radio (NR) technology are oriented to provide services of desired quality (QoS), it becomes questionable how to model and predict targeted QoS values, especially if the physical channel is dynamically changing. In order to overcome mobility issues, we aim to support the evaluation of second-order statistics of signal, namely level-crossing rate (LCR) and.

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NYUSIM Version 1.4 Now Available - NYU WIRELES

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