Rapidly converging low-complexity iterative transmit precoders for massive MIMO downlink
Rapidly converging low-complexity iterative transmit precoders for massive MIMO downlink
In this paper, rapidly converging low-complexity iterative transmit precoding (TPC) techniques are proposed for the massive multiple-input multiple-output (MIMO) downlink. First of all, the proposed random block-based iterative TPC (RBI-TPC) algorithm performs its iterations by updating multiple rather than a single component at each instant, where the updating order of each block containing multiple components relies on the samples randomly sampled from a discrete distribution. Based on the analytically derived convergence rate, we demonstrate that improved convergence is achieved by the block-based update mechanism conceived since the correlation between multiple components can be beneficially exploited. Then, the random sampling that determines the updating order is studied. By applying conditional random sampling, the updating order is optimized based on the latest updates for attaining more rapid convergence. We also demonstrate that the associated updating order may become deterministic under specific conditions so that a fixed but optimized updating order can be used for facilitating the practical implementations, which paves the way for conceiving the ordered block-based iterative TPC (OBI-TPC) algorithm. Finally, the concept of successive over-relaxation (SOR) is adopted for further convergence improvement and simulations are presented to illustrate the performance improvements of the proposed RBI and OBI TPC algorithms compared to the existing low-complexity iterative TPC schemes.
Convergence, Downlink, Iterative algorithms, Jacobian matrices, Massive MIMO, Precoding, Symmetric matrices, iterative methods, low-complexity linear transmit precoding, random sampling
7228-7243
Wang, Zheng
e272fcba-3d0e-463e-b12c-91156b281197
Wang, Jiaheng
bb3ee4a5-5f1c-4c6e-a800-33857648280d
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Huang, Yongming
65b6f657-0290-4884-81ce-a9cb5b536b99
Ng, Derrick Wing Kwan
8e2a32d3-cb0d-4c38-b05c-03ef16a5c707
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
1 December 2023
Wang, Zheng
e272fcba-3d0e-463e-b12c-91156b281197
Wang, Jiaheng
bb3ee4a5-5f1c-4c6e-a800-33857648280d
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Huang, Yongming
65b6f657-0290-4884-81ce-a9cb5b536b99
Ng, Derrick Wing Kwan
8e2a32d3-cb0d-4c38-b05c-03ef16a5c707
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Wang, Zheng, Wang, Jiaheng, Gao, Zhen, Huang, Yongming, Ng, Derrick Wing Kwan and Hanzo, Lajos
(2023)
Rapidly converging low-complexity iterative transmit precoders for massive MIMO downlink.
IEEE Transactions on Communications, 71 (12), .
(doi:10.1109/TCOMM.2023.3305646).
Abstract
In this paper, rapidly converging low-complexity iterative transmit precoding (TPC) techniques are proposed for the massive multiple-input multiple-output (MIMO) downlink. First of all, the proposed random block-based iterative TPC (RBI-TPC) algorithm performs its iterations by updating multiple rather than a single component at each instant, where the updating order of each block containing multiple components relies on the samples randomly sampled from a discrete distribution. Based on the analytically derived convergence rate, we demonstrate that improved convergence is achieved by the block-based update mechanism conceived since the correlation between multiple components can be beneficially exploited. Then, the random sampling that determines the updating order is studied. By applying conditional random sampling, the updating order is optimized based on the latest updates for attaining more rapid convergence. We also demonstrate that the associated updating order may become deterministic under specific conditions so that a fixed but optimized updating order can be used for facilitating the practical implementations, which paves the way for conceiving the ordered block-based iterative TPC (OBI-TPC) algorithm. Finally, the concept of successive over-relaxation (SOR) is adopted for further convergence improvement and simulations are presented to illustrate the performance improvements of the proposed RBI and OBI TPC algorithms compared to the existing low-complexity iterative TPC schemes.
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lajos (8)
- Accepted Manuscript
More information
Accepted/In Press date: 7 August 2023
e-pub ahead of print date: 15 August 2023
Published date: 1 December 2023
Additional Information:
Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61801216, 62371124, 61720106003, 62225107, 61971130 and U22B2006
Publisher Copyright:
© 1972-2012 IEEE.
Keywords:
Convergence, Downlink, Iterative algorithms, Jacobian matrices, Massive MIMO, Precoding, Symmetric matrices, iterative methods, low-complexity linear transmit precoding, random sampling
Identifiers
Local EPrints ID: 481018
URI: http://eprints.soton.ac.uk/id/eprint/481018
ISSN: 0090-6778
PURE UUID: 3f30f379-ca8e-4bab-8c5c-c52296ae49d6
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Date deposited: 14 Aug 2023 17:13
Last modified: 18 Mar 2024 05:13
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Contributors
Author:
Zheng Wang
Author:
Jiaheng Wang
Author:
Zhen Gao
Author:
Yongming Huang
Author:
Derrick Wing Kwan Ng
Author:
Lajos Hanzo
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