Analysis of IRS-Assisted Downlink Wireless Networks Over Generalized Fading

Intelligent Reflecting Surface (IRS) is a communication technology that can control the phase shift and reflection of the incoming signal towards the destination, achieving high spectral efficiency at a low hardware cost. However, the IRS-assisted wireless networks pose fundamental challenges on sta...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2024-08, Vol.23 (8), p.10182-10197
Main Authors: Li, Yunli, Chun, Young Jin
Format: Article
Language:English
Subjects:
Accuracy
Analytical models
Approximation
cascaded channel
Communication
Cost analysis
Frequencies
Gamma distribution
generalized fading
Intelligent reflecting surface
Interference
mixture channel
mixture Gamma distribution
Mixtures
Parameterization
Probability density function
Probability distribution functions
Quadratic forms
Rayleigh channels
Reconfigurable intelligent surfaces
Signal reflection
Statistical analysis
stochastic geometry
Stochastic processes
Wireless communications
Wireless networks
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Summary:Intelligent Reflecting Surface (IRS) is a communication technology that can control the phase shift and reflection of the incoming signal towards the destination, achieving high spectral efficiency at a low hardware cost. However, the IRS-assisted wireless networks pose fundamental challenges on statistical channel modeling. Communication assisted by the IRS takes the form of a mixture channel, composed of a direct link and cascaded link aided by the IRS, which is often intractable to analyze, requires advanced functions, such as Meijer's G or Fox's H functions, to describe, and only applies to a certain operating frequency or network environment. These limitations motivate the development of a tractable and highly accurate channel model for IRS-assisted wireless networks, but versatile enough to be applied to any frequency band and communication scenario given proper parameterization. To this end, we utilize the mixture Gamma distributions to model IRS-assisted communication and derive distributions of the mixture channel for both multiplicability and quadratic form. The system performance of the IRS-assisted wireless network is analyzed using stochastic geometry, and the approximation accuracy of the proposed channel model is validated through extensive numerical simulation. These results indicate that the mixture Gamma distribution-based approximation can greatly facilitate the modeling and analysis in IRS-assisted networks with high accuracy.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2024.3369662