Parallelizable First-Order Fast Algorithm for Symbol-Level Precoding in Lage-Scale Systems
We investigate constructive interference (CI)-based symbol-level precoding (SLP) in large-scale systems with massive connectivity of users to minimize the transmit power subject to the instantaneous signal-to-interference-plus-noise-ratio (SINR) and CI constraints. By converting the considered probl...
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| Vydané v: | IEEE Vehicular Technology Conference s. 1 - 6 |
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01.06.2023
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| Abstract | We investigate constructive interference (CI)-based symbol-level precoding (SLP) in large-scale systems with massive connectivity of users to minimize the transmit power subject to the instantaneous signal-to-interference-plus-noise-ratio (SINR) and CI constraints. By converting the considered problem into a novel separable formulation, we reveal the existence of separability in SLP, which is therefore well-suited for decomposition. The proximal Jacobian alternating direction method of multipliers (PJ-ADMM) framework is adopted to decompose the reformulated problem into multiple subproblems, which can be solved in parallel with closed-form solutions. We further linearize the second-order terms by approximation, which leads to a parallelizable first-order fast solution to SLP. Our derivations are validated by simulation results, which also show that our algorithm can provide optimal performance with substantially lower computational complexity than state-of-the-art algorithms. |
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| AbstractList | We investigate constructive interference (CI)-based symbol-level precoding (SLP) in large-scale systems with massive connectivity of users to minimize the transmit power subject to the instantaneous signal-to-interference-plus-noise-ratio (SINR) and CI constraints. By converting the considered problem into a novel separable formulation, we reveal the existence of separability in SLP, which is therefore well-suited for decomposition. The proximal Jacobian alternating direction method of multipliers (PJ-ADMM) framework is adopted to decompose the reformulated problem into multiple subproblems, which can be solved in parallel with closed-form solutions. We further linearize the second-order terms by approximation, which leads to a parallelizable first-order fast solution to SLP. Our derivations are validated by simulation results, which also show that our algorithm can provide optimal performance with substantially lower computational complexity than state-of-the-art algorithms. |
| Author | Li, Ang Yang, Junwen Masouros, Christos Liao, Xuewen |
| Author_xml | – sequence: 1 givenname: Junwen surname: Yang fullname: Yang, Junwen email: jwyang@stu.xjtu.edu.cn organization: Xi'an Jiaotong University,School of Information and Communications Engineering,Xi'an,China – sequence: 2 givenname: Ang surname: Li fullname: Li, Ang email: ang.li.2020@xjtu.edu.cn organization: Xi'an Jiaotong University,School of Information and Communications Engineering,Xi'an,China – sequence: 3 givenname: Xuewen surname: Liao fullname: Liao, Xuewen email: yeplos@mail.xjtu.edu.cn organization: Xi'an Jiaotong University,School of Information and Communications Engineering,Xi'an,China – sequence: 4 givenname: Christos surname: Masouros fullname: Masouros, Christos email: c.masouros@ucl.ac.uk organization: University College London,Department of Electronic and Electrical Engineering,London,UK |
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| Snippet | We investigate constructive interference (CI)-based symbol-level precoding (SLP) in large-scale systems with massive connectivity of users to minimize the... |
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| SubjectTerms | ADMM Approximation algorithms constructive interference Downlink Interference Jacobian matrices Massive MU-MISO parallel and distributed computing Precoding separability Simulation symbol-level precoding Vehicular and wireless technologies |
| Title | Parallelizable First-Order Fast Algorithm for Symbol-Level Precoding in Lage-Scale Systems |
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