Large-Scale Beamforming for Massive MIMO via Randomized Sketching
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| Title: | Large-Scale Beamforming for Massive MIMO via Randomized Sketching |
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| Authors: | Hayoung Choi, Tao Jiang, Yuanming Shi, Xuan Liu, Yong Zhou, Khaled B. Letaief |
| Source: | IEEE Transactions on Vehicular Technology. 70:4669-4681 |
| Publisher Information: | Institute of Electrical and Electronics Engineers (IEEE), 2021. |
| Publication Year: | 2021 |
| Subject Terms: | Regularized zero-forcing beamforming, 0202 electrical engineering, electronic engineering, information engineering, Sketching method, 02 engineering and technology, Massive MIMO, Randomized sketching algorithm, 7. Clean energy |
| Description: | Massive MIMO system yields significant improvements in spectral and energy efficiency for future wireless communication systems. The regularized zero-forcing (RZF) beamforming is able to provide good performance with the capability of achieving numerical stability and robustness to the channel uncertainty. However, in massive MIMO systems, the matrix inversion operation in RZF beamforming becomes computationally expensive. To address this computational issue, we shall propose a novel randomized sketching based RZF beamforming approach with low computational complexity. This is achieved by solving a linear system via randomized sketching based on the preconditioned Richard iteration, which guarantees high quality approximations to the optimal solution. We theoretically prove that the sequence of approximations obtained iteratively converges to the exact RZF beamforming matrix linearly fast as the number of iterations increases. Also, it turns out that the system sum-rate for such sequence of approximations converges to the exact one at a linear convergence rate. Our simulation results verify our theoretical findings. |
| Document Type: | Article |
| ISSN: | 1939-9359 0018-9545 |
| DOI: | 10.1109/tvt.2021.3071543 |
| Access URL: | http://arxiv.org/pdf/1903.05904 https://arxiv.org/abs/1903.05904 https://dblp.uni-trier.de/db/journals/tvt/tvt70.html#ChoiJSLZL21 http://ieeexplore.ieee.org/document/9398557 https://ieeexplore.ieee.org/document/9398557 https://www.arxiv-vanity.com/papers/1903.05904/ https://doi.org/10.1109/TVT.2021.3071543 |
| Rights: | IEEE Copyright |
| Accession Number: | edsair.doi.dedup.....5e82b08306bb43bdcc68ef5e9808c0af |
| Database: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstract: | Massive MIMO system yields significant improvements in spectral and energy efficiency for future wireless communication systems. The regularized zero-forcing (RZF) beamforming is able to provide good performance with the capability of achieving numerical stability and robustness to the channel uncertainty. However, in massive MIMO systems, the matrix inversion operation in RZF beamforming becomes computationally expensive. To address this computational issue, we shall propose a novel randomized sketching based RZF beamforming approach with low computational complexity. This is achieved by solving a linear system via randomized sketching based on the preconditioned Richard iteration, which guarantees high quality approximations to the optimal solution. We theoretically prove that the sequence of approximations obtained iteratively converges to the exact RZF beamforming matrix linearly fast as the number of iterations increases. Also, it turns out that the system sum-rate for such sequence of approximations converges to the exact one at a linear convergence rate. Our simulation results verify our theoretical findings. |
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| ISSN: | 19399359 00189545 |
| DOI: | 10.1109/tvt.2021.3071543 |