# Fifth-Generation (5G) mmWave Spatial Channel Characterization for Urban Environments’ System Analysis

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## Abstract

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## 1. Introduction

## 2. Background

## 3. Wireless Channel Characterization

#### 3.1. Deterministic 3D Ray Launching Algorithm

#### 3.2. Scenario Description

#### 3.3. Large-Scale Propagation

#### 3.4. Small-Scale Propagation

#### 3.5. Statistical Analysis

#### 3.6. Interference Analysis

## 4. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**(

**a**) Conductivity as a function of frequency for different materials, (

**b**) Relative permittivity as a function of frequency for different materials.

**Figure 2.**Schematic view of the Three-Dimensional Ray-Launching (3D-RL) algorithm implemented modules.

**Figure 3.**Real aerial view of the considered scenario alongside the schematic representation of the simulated scenarios (outdoor and indoor) and the employed 3D ray-launching parameters for each of the considered scenarios.

**Figure 4.**Bi-dimensional plane of received power [dBm] for a 1.3 m height with the position of the measurements points and transmitter position highlighted.

**Figure 6.**Simulated mmWave power distribution for outdoor coverage (at 28 GHz, beam width values of 80° and 20°, with 180° and 90° orientation), under simulation parameters defined in Table 2.

**Figure 7.**Simulated mmWave power distribution for indoor coverage (at 60 GHz, beam width values of 45°, 80° and 180°, 270° antenna orientation), under simulation parameters defined in Table 2.

**Figure 8.**Root-mean-square (RMS) delay spread for 20° and 80° radiation pattern with 180° orientation, for a height of 1.3 m with its associated Power Delay Profile for a specific point in the scenario.

**Figure 9.**Coherence bandwidth for the outdoor scenario (80° beam width and 180° antenna orientation) at the bi-dimensional plane of 1.3 m height.

**Figure 10.**Kolmogorov–Smirnov statistic between the data from simulation and Nakagami distribution (

**top left**), Rayleigh distribution (

**top right**), Weibull distribution (

**center left**), Log-normal distribution (

**center right**), and Gamma distribution (

**bottom**) for the outdoor scenario and different transmitter antenna configurations.

**Figure 11.**Best fitted distribution for the outdoor scenario (at 28 GHz, beam width values of 80° and 20°, with 180° and 90° orientation) at the bi-dimensional plane of 1.3 m height.

**Figure 12.**Log-normal distribution’s µ (

**top**) and $\sigma $ (

**bottom**) parameters for the 80° beam width outdoor scenarios.

**Figure 13.**Weibull distribution’s $a$ (

**top**) and $b$ (

**bottom**) parameters for the 20° beam width outdoor scenarios.

**Figure 14.**Kolmogorov–Smirnov statistic between the data from simulation and Nakagami distribution (

**top left**), Rayleigh distribution (

**top right**), Weibull distribution (

**center left**), Log-normal distribution (

**center right**), and Gamma distribution (

**bottom**), for the indoor scenarios.

**Figure 17.**Signal-to-noise ratio [dB] for a bi-dimensional plane of the considered outdoor scenario with 14 interfering antennas (

**white dots**) and its associated Bit Error Probability (BER) for two transmitter-receiver (TX-RX) linear radials (

**red dashed lines**) along X-axis and Y-axis for a Single-Carrier Modulation Carrier Scheme 12 (SC MCS-12), 16-QAM modulation scheme.

Ref | Description | Results | Freq. |
---|---|---|---|

[17] | 3D mmWave statistical channel model | Extraction of a statistical channel impulse response model to obtain spatio-temporal characterization | 28 GHz/73 GHz |

[18] | Semi-deterministic modeling based on ray tracing (RT) and graph theory | Multipath radio propagation is modelled with the aid of a graph theory-based approach, in which scatterers are modelled with realistic scenario elements. | 3.8 GHz/60 GHz |

[22] | Wireless channel characterization in Fifth-Generation (5G) mmWave railway communications | Wireless channel characterization for different types of scenarios of operation (urban, rural, tunnel) are performed with the aid of RT and measurement results. | 25.25 GHz |

[23,24] | Micro-cell urban (UMi) wireless channel modeling | Path loss model parameters are proposed employing random variables to consider channel dynamics. 3D RT is employed in [16] to obtain UMi wireless channel characterization | 28 GHz |

[28,29,30,31,32,33,34] | Indoor characterization | Deterministic RT techniques are employed to characterize directional beam forming behavior in small indoor environments. Multiple-input-multiple-output (MIMO) behavior is analyzed, as well as multiple models proposed for different frequency ranges. | 5 GHz/28 GHz/31 GHz/70 GHz/90 GHz |

[35,36,37] | Vehicular wireless communication channel characterization | Multiple aspects such as V2V/V2I wireless channel characterization or the impact of urban infrastructure and tunnels is addressed | mmWave/79 GHz/300 GHz |

[38,39,40,41] | Topological and environmental impact in wireless channel characterization | Topological aspects, such as scenario type and beamforming characteristics are analyzed, the impact of environmental factors such as rain and the consideration of EMF compliance in wireless planning and analysis are described. | FR1/32 GHz/73 GHz/83 GHz |

[42,43] | Application of artificial intelligence (AI) techniques in 5G mmWave wireless channel characterization | Different AI-based techniques are described in order to enhance functionalities such as beam forming or interference analysis, related with wireless channel characterization | Generalizable |

Parameters | Outdoor Validation (Case I) | Outdoor Simulation (Case II) | Indoor Simulation (Case III) |
---|---|---|---|

Transmitted Power | 36 dBm | 10 dBm | 10 dBm |

Operation Frequency | 30 GHz | 28 GHz | 60 GHz |

Antenna beam width | Omnidirectional Monopole | 80°/20° | 180°/80°/45° |

Transmitted data rate | 100 Mbps | 4.62 Gbps | 4.62 Gbps |

3D RL Resolution | 1° | 1° | 1° |

Reflections | 6 | 6 | 6 |

Scenario size (m) | 135 × 70 × 18 | 92.2 × 70 × 15 | 5.84 × 6.24 × 3.5 |

Unitary volume analysis | 1 m | 1 m | 0.1 m |

Transmitter Position (m) | (78.7, 40.3, 1.3) | (87.8, 32.9, 4) | (3.5, 5.8, 1.05) |

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## Share and Cite

**MDPI and ACS Style**

Azpilicueta, L.; Lopez-Iturri, P.; Zuñiga-Mejia, J.; Celaya-Echarri, M.; Rodríguez-Corbo, F.A.; Vargas-Rosales, C.; Aguirre, E.; Michelson, D.G.; Falcone, F. Fifth-Generation (5G) mmWave Spatial Channel Characterization for Urban Environments’ System Analysis. *Sensors* **2020**, *20*, 5360.
https://doi.org/10.3390/s20185360

**AMA Style**

Azpilicueta L, Lopez-Iturri P, Zuñiga-Mejia J, Celaya-Echarri M, Rodríguez-Corbo FA, Vargas-Rosales C, Aguirre E, Michelson DG, Falcone F. Fifth-Generation (5G) mmWave Spatial Channel Characterization for Urban Environments’ System Analysis. *Sensors*. 2020; 20(18):5360.
https://doi.org/10.3390/s20185360

**Chicago/Turabian Style**

Azpilicueta, Leyre, Peio Lopez-Iturri, Jaime Zuñiga-Mejia, Mikel Celaya-Echarri, Fidel Alejandro Rodríguez-Corbo, Cesar Vargas-Rosales, Erik Aguirre, David G. Michelson, and Francisco Falcone. 2020. "Fifth-Generation (5G) mmWave Spatial Channel Characterization for Urban Environments’ System Analysis" *Sensors* 20, no. 18: 5360.
https://doi.org/10.3390/s20185360