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- W4387123225 abstract "Intelligent reflecting surface (IRS) has been put forward as one of the key candidate technologies to achieve high spectrum efficiency. However, to reach its full potential there is a need for the availability of accurate channel state information, which is quite challenging to estimate. This paper, therefore, focuses on proposing two compressive sensing algorithm-based channel estimation schemes to be used in the IRS-aided millimeter wave (mmWave) wireless communication systems. The first channel estimation named reduced complexity-orthogonal matching pursuit (OMP) (RedCOMP)-based channel estimation scheme seeks to achieve optimum performance while reducing the computational complexity associated with the traditional OMP algorithm. The second scheme named remodelled OMP (RemOMP)-based channel estimation method aims at obtaining enhanced channel estimate with the aid of side information known a priori at the receiver. Simulation results indicate that the proposed RemOMP-based channel estimator exhibits the best performance among the three channel estimation schemes with similar computational complexity cost to the traditional OMP-base channel estimator. However, the RedCOMP-based channel estimation scheme, while not showing good performance, incurred the least computational complexity cost among all the schemes." @default.
- W4387123225 created "2023-09-29" @default.
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- W4387123225 date "2023-09-06" @default.
- W4387123225 modified "2023-10-18" @default.
- W4387123225 title "Remodelled and Reduced complexity-OMP-based Channel Estimation Schemes for Intelligent Reflecting Surface-Aided Millimeter Wave Systems" @default.
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- W4387123225 doi "https://doi.org/10.1109/icspcs58109.2023.10261140" @default.
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