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Coverage Enhancement in Millimeter-Wave Cellular Networks via Distributed IRSs

Xiaoming Shi, Na Deng, Nan Zhao, Dusit Niyato

2022IEEE Transactions on Communications32 citationsDOI

Abstract

Intelligent reflecting surface (IRS) is a promising technology to provide line-of-sight (LOS) links for blocked paths, especially in millimeter wave (mmWave) cellular networks. However, in practice, it is difficult for IRSs to arbitrarily adjust the reflection angle to align served users. A promising solution is to deploy distributed IRSs to increase the probability that the users lie in the reflection directions. This paper develops a stochastic geometry-based approach for studying the coverage enhancement in mmWave cellular networks via distributed IRSs. Specifically, the locations of IRSs are modeled through a binomial point process centered at a base station, and the reflection beam of each IRS is pointed to a certain direction. Considering the difference between LOS and non-LOS mmWave transmissions, we propose a received signal strength indicator based association strategy to guarantee that the users receive the strongest average power. After characterizing the association probabilities and distance distributions, we derive the coverage probability for an arbitrary user and perform simplifications for enhancing the computation efficiency. The results are validated by simulations and reveal that distributed deployment of IRSs can achieve a better coverage probability than that of the centralized deployment, which validates the feasibility of enhancing system performance through distributed IRSs.

Topics & Concepts

Computer scienceStochastic geometryCellular networkCoverage probabilitySoftware deploymentExtremely high frequencyBase stationReflection (computer programming)Distributed antenna systemComputationDistributed computingReal-time computingComputer networkTelecommunicationsAlgorithmMathematicsOperating systemStatisticsConfidence intervalProgramming languageAdvanced Wireless Communication TechnologiesMillimeter-Wave Propagation and ModelingIndoor and Outdoor Localization Technologies
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