Isarithmic mapping of radio-frequency noise in the urban environment

Haedrich, Caitlin E.; Breton, Daniel J.; Wilson, David C.

doi:10.21079/11681/37959

Cited by 2 publications

(3 citation statements)

References 14 publications

(24 reference statements)

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“…Thus, a linear correction to the RSSI maps could be considered to account for the average temperature, following previously identified dependences of the signal-coverage on weather parameters. (3) Effect of RF noise: Previous works demonstrate that high-levels of RF noise can be found in urban environments [62]. However, LoRa's modulation characteristics make it particularly invulnerable to noise interference [54], and thus, we neglected such effects in our approximation.…”

Section: Discussionmentioning

confidence: 99%

Cityscape LoRa Signal Propagation Predicted and Tested Using Real-World Building-Data Based O-FDTD Simulations and Experimental Characterization

Adão

Balvís²,

Carpentier

et al. 2021

Sensors

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The age of the Internet of Things (IoT) and smart cities calls for low-power wireless communication networks, for which the Long-Range (LoRa) is a rising star. Efficient network engineering requires the accurate prediction of the Received Signal Strength Indicator (RSSI) spatial distribution. However, the most commonly used models either lack the physical accurateness, resolution, or versatility for cityscape real-world building distribution-based RSSI predictions. For this purpose, we apply the 2D electric field wave-propagation Oscillator Finite-Difference Time-Domain (O-FDTD) method, using the complex dielectric permittivity to model reflection and absorption effects by concrete walls and the receiver sensitivity as the threshold to obtain a simulated coverage area in a 600 × 600 m2 square. Further, we report a simple and low-cost method to experimentally determine the signal coverage area based on mapping communication response-time delays. The simulations show a strong building influence on the RSSI, compared against the Free-Space Path (FSPL) model. We obtain a spatial overlap of 84% between the O-FDTD simulated and experimental signal coverage maps. Our proof-of-concept approach is thoroughly discussed compared to previous works, outlining error sources and possible future improvements. O-FDTD is demonstrated to be most promising for both indoors and outdoors applications and presents a powerful tool for IoT and smart city planners.

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Section: Discussionmentioning

confidence: 99%

Cityscape LoRa Signal Propagation Predicted and Tested Using Real-World Building-Data Based O-FDTD Simulations and Experimental Characterization

Adão

Balvís²,

Carpentier

et al. 2021

Sensors

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“…1. All noise sources are treated as point sources (Haedrich et al, 2020), 2. All noise sources are identical, and radiate isotopically with equal power q 0 , 3.…”

Section: Modelmentioning

confidence: 99%

“…To begin, the following assumptions are made: All noise sources are treated as point sources (Haedrich et al., 2020), All noise sources are identical, and radiate isotopically with equal power q 0 , The sources are located along a 1‐D line segment in a completely spatially random (CSR) way, Source‐to‐receiver path losses follow a log‐distance relationship (Rappaport, 2010, Chapter 4) with a path loss exponent γ , and Power from multiple noise sources is completely incoherent and additive. …”

Section: Modelmentioning

confidence: 99%

Spatial Structure of the Radio‐Frequency Noise Field in a Large City

Meyer,

Breton,

Kamrath

et al. 2024

Radio Science

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The urban radio‐frequency (RF) noise generated by our cities continues to change with time. Although models exist to describe the RF noise as functions of frequency and urban land use types, very few models describe the spatial character or structure of the noise on the scales of city blocks (50–150 m). The goal of this work is to investigate the connection between urban morphology and the higher‐order spatial statistics of the noise field. To achieve this goal, a large measurement campaign was conducted in Boston, Massachusetts. Many spatial measurements allowed for calculation of spatial correlation functions of noise power in three different neighborhoods, which were used to quantify the spatial structure of the fields. A statistical point source model is then developed, with adjustable parameters relating to urban morphology. Good agreement between the model and the experimental correlation functions suggests the 25 MHz urban noise field is well described by a random network of fixed point sources, radiating with a 1/r power law behavior.

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Isarithmic mapping of radio-frequency noise in the urban environment

Cited by 2 publications

References 14 publications

Cityscape LoRa Signal Propagation Predicted and Tested Using Real-World Building-Data Based O-FDTD Simulations and Experimental Characterization

Cityscape LoRa Signal Propagation Predicted and Tested Using Real-World Building-Data Based O-FDTD Simulations and Experimental Characterization

Spatial Structure of the Radio‐Frequency Noise Field in a Large City

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