This paper investigates the application of machine learning for optimal deployment of 5G infrastructure, such as the position and the orientation of the antenna that help achieve the best signal coverage. This avoids the need to perform on-site measurements or extensive software simulations. Multivariate Regression (MR) and Neural Network (NN) models are applied to predict the signal coverage in an indoor environment. The results show that the average prediction error using NN for the case investigated is 7 dB for a 60-GHz operating frequency, whereas the error using the MR technique is lower than 6 dB. The unique aspect in the investigation is the integration of the clustering algorithm and the NN machine learning model for predicting indoor signal coverage.
Remcom's, Tarun Chawla, was a guest on the Sciencei Podcast. Tarun discussed the revolutionary technologies...
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This short video clip demonstrates how Wireless InSite models engineered EM surfaces (EES) and compares coverage improvement with diffuser and grating EES placements on a glass window or a wall.
In this whitepaper, we use Wireless InSite to provide a realistic assessment of radar altimeter interference due to emissions from 5G base stations.
This article explores the effectiveness of massive MIMO beamforming at mitigating the challenges expected from using the expanse of spectrum available in the mmWave band.
Remcom's, Tarun Chawla, was a guest on the Sciencei Podcast. Tarun discussed the revolutionary technologies in wireless communications that have been developed during the past decades.
This webinar demonstrates the strengths of XFdtd and Wireless InSite for designing and simulating smart home devices.
Wireless InSite predicts the coverage and interference and accounts for the multipath in complex environments such as heavy-industrial factories, warehouses, server farms and more.
This booklet explores the core numerical methods utilized in Remcom’s software products.
In this video tutorial series, we walk through a step-by-step outdoor propagation analysis using Wireless InSite MIMO.
A passenger train located in a station is connected to an access point (AP) mounted on the roof of the station. RF propagation paths computed using the shooting-and-bouncing ray technique are shown.
In this presentation, an example showcasing Wireless InSite's novel diffuse scattering technique is applied to an office environment at 73 GHz and is compared against measurements.
This simulation shows the coverage prediction from LTE sites in a suburban downtown area. With the emergence of 5G, Fixed Wireless Access and small cell mobile service can be provided.
Wireless InSite’s ray-tracing was used to analyze signal propagation in a complex urban scenario. These coverage results highlight potential obstacles and solutions for deployment of mmWave for 5G.
In this video tutorial, we offer a step-by-step guide to perform an indoor propagation analysis in an enterprise environment.
This article describes the modeling of a SATCOM link, specifically the use case of using a satellite overlay to extend service continuity to IoT devices in a poorly covered rural area.
Professor Ram Narayanan of Penn State's College of Engineering worked with Remcom to produce a 5G millimeter wave coverage concept using existing AT&T towers in State College, PA.
This presentation demonstrates a predictive capability for simulating massive MIMO antennas and beamforming in dense urban propagation environments.
This presentation demonstrates a new predictive tool for simulating FD-MIMO in urban environments. We analyze predicted multipath and compare performance of beamforming techniques.
This example demonstrates how a custom beamforming table can be used to model downlink data rates from three MIMO base stations for 5G New Radio in a section of Boston.
Learn about Wireless InSite, key features and output, and the MIMO version of the product.
This collection of application examples demonstrates how REmcom's EM simulation software solves challenges related to 5G and MIMO.