Supercomputing-Enabled First-Principles Analysis of Radio Wave Propagation in Urban Environments

MacKie-Mason, Brian; Shao, Yang; Greenwood, Andrew; Peng, Zhen

doi:10.1109/tap.2018.2874674

Cited by 15 publications

(6 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After reviewing the literature [26]- [31], the authors summarize the existing wireless spatial channels. The energy efficiency of the channel matrix coding design that is closest to the forest environment space is shown in Fig.…”

Section: Wireless Communication Depends On Wireless Channelsmentioning

confidence: 99%

Improvement of the Spatial Channel Matrix Mapping and Precoding Algorithm in the Forest Environment

Zhang

Wang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Few studies have been conducted on the forest spatial channel matrix, most of which were conducted by experts and scholars in the field of communications. The mature cellular network channel coding matrix was ''transplanted'' to the vegetation-covered space, and the effects of the various vegetation dielectric constants, the forest canopy density and other objective factors on the traditional cellular channel were ignored. To overcome this problem, this paper built a relay network that is suitable for forest environments. This network was an effective complement to the existing cellular communication network for expanding the coverage of signals in the forest. On this basis, this paper analysed the multi-antenna relay transmission protocol and proposed an additional spatial channel matching (mapping) matrix between the forward and backward filters. This matrix was designed to consider the effect of the complex forest environment on the channel to reduce the relaying noise power. Then, under the forest cellular relay network topology, a spatial channel matrix structure (based on unitary matrix) that is suitable for the forest environment is proposed. This matrix can be incorporated into various relay protocols and considers the source node preprocessing operation and the destination node equalizer. The forest relay cooperative network that is proposed in this paper can effectively expand the coverage of signals in forest areas; however, due to the inherent limitations of the relay network, many problems will be encountered in practical applications. For example, the precoding scheme that is based on phase correction requires the terminal node to feed the phase correction factor back to the forest base station node; however, the system performance is substantially affected by the feedback accuracy and the arrival delay difference. Due to the uncertain rank of the integrated channel in the forest base station precoding scheme, it was necessary to adapt to a variety of antenna ports, which rendered the design of the precoding codebook highly difficult. In addition, when the number of transmission layers was greater than 1, the local precoding scheme also encountered the problem of inter-layer interference (ILI). Based on a detailed analysis of the shortcomings of the previous scheme and the strategy of partial coherence transmission, this paper proposes an improved algorithm of incoherent joint transmission technology and an improved precoding scheme that are suitable for forest relay systems. The signal that is transmitted by the relay node and the feedback signal is corrected via layer exchange between cells and via phase correction. By changing the layer's exchange information and phase information, it can be adapted to various forest environments, such as artificial forests, natural forests, and virgin forests. Finally, the outage probability is considered as a performance indicator in the simulation of the forest environment wireless relay system. The theoretical analysis and simulation results demonstrate the s...

show abstract

Section: Wireless Communication Depends On Wireless Channelsmentioning

confidence: 99%

Improvement of the Spatial Channel Matrix Mapping and Precoding Algorithm in the Forest Environment

Zhang

Wang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Propagation models can be derived by physics-based methods such as ray-tracing [2][3][4], the vector parabolic equation (VPE) [5,6] or even full-wave electromagnetic analysis techniques [7]. For radio propagation in tunnels, analytical models based on waveguide mode theory [8] were first used.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network models for radiowave propagation in tunnels

Seretis

Zhang

Zeng

et al. 2020

IET Microwaves, Antennas & Propagation

View full text Add to dashboard Cite

The authors present a machine learning approach for the extraction of radiowave propagation models in tunnels. To that end, they discuss three challenges related to the application of machine learning to general wireless propagation problems: how to efficiently specify the input to the model, which learning method to use and what output functions to seek. The input that any propagation modelling tool (be it a ray‐tracer, a full‐wave method or a parabolic equation solver) uses, can be considered as visual, in the form of an image or a point cloud of the environment under consideration. Therefore, they propose an artificial neural network structure that generalises well to various geometries. The desired output can be values of the electromagnetic field components across the channel or just a path loss model. They apply these ideas to the case of arched tunnels for the first time. They consider cases where the geometric parameters of the tunnel, the position of the receiver and the frequency of operation are parts of a model trained by a vector parabolic equation solver. The model is evaluated using solver‐generated as well as measured data. The numerical results demonstrate that this approach combines computational efficiency with high accuracy.

show abstract

“…In the last years, the capabilities of computational resources have increased almost exponentially. The field of computational electromagnetics (CEM) have also benefited from this trend, solving large problems which were unreachable a few years before 1,2 …”

Section: Introductionmentioning

confidence: 99%

A testbench of arbitrary accuracy for electromagnetic simulations

Amor-Martín

2020

Int J RF Microw Comput Aided Eng

View full text Add to dashboard Cite

Several electromagnetic problems for verification purposes in computational electromagnetics are introduced. Details about the formulation of a generalized eigenvalue problem for non‐lossy and lossy materials are provided to obtain a fast and ready‐to‐use way of verification. Codes written using the symbolic toolbox from MATLAB are detailed to obtain an arbitrary accuracy for the proposed problems. Finally, numerical results in a finite element method code are presented together with the analytical values to show the accuracy of the code proposed.

show abstract

Supercomputing-Enabled First-Principles Analysis of Radio Wave Propagation in Urban Environments

Cited by 15 publications

References 70 publications

Improvement of the Spatial Channel Matrix Mapping and Precoding Algorithm in the Forest Environment

Improvement of the Spatial Channel Matrix Mapping and Precoding Algorithm in the Forest Environment

Artificial neural network models for radiowave propagation in tunnels

A testbench of arbitrary accuracy for electromagnetic simulations

Contact Info

Product

Resources

About