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- W2612733041 abstract "Next-generation cellular network may encounter unprecedented challenges, while cloud radio access network (C-RAN) is regarded as a promising network architecture to meet the explosive growth of data traffic. In C-RAN, all the signal processing is shifted to the cloud data center to realize joint resource allocation and interference management, which highly relies on the accuracy of channel state information (CSI). However, the assumption of perfect CSI can hardly be secured, especially in dense network scenario. Meanwhile, for dense CRAN, the network optimization will be further confined by curse of dimensionality. In this paper, we propose an adaptive RRH switch-off mechanism through an iterative reweighted sparse beamforming (IrSBF), which only depends on imperfect CSI and has certain endurance to the outage of S!NR. However, the non-convex ℓ <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>0</sub> -norm optimization and probabilistic SINR constraints make the beamforming design highly intractable. Utilizing the Bernstein-type inequality to transform the chance constraints to conservative static constraints, we are able to solve the robust sparse beamforming problem through semidefinite relaxation (SDR) technology. Besides, ℓ <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sub> -norm approximation method is used to design the sparse beamforming vector for users iteratively. Simulation results suggest that the proposed IrSBF algorithm significantly outperforms the conventional coordinated beamforming (CB) solution and group sparse beamforming (GSBF) algorithm ignoring CS! errors, especially in the case of higher network density." @default.
- W2612733041 created "2017-05-19" @default.
- W2612733041 creator A5025686930 @default.
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- W2612733041 date "2017-03-01" @default.
- W2612733041 modified "2023-09-25" @default.
- W2612733041 title "Robust Group Sparse Beamforming for Dense C-RANs with Probabilistic SINR Constraints" @default.
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- W2612733041 doi "https://doi.org/10.1109/wcnc.2017.7925637" @default.
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