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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Vydáno v:IEEE Vehicular Technology Conference s. 1 - 6
Hlavní autoři: Yang, Junwen, Li, Ang, Liao, Xuewen, Masouros, Christos
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2023
Témata:
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
ISSN:2577-2465
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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.
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
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  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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