Hierarchical Functionality Prioritization in Multicast ISAC: Optimal Admission Control and Discrete-Phase Beamforming

We investigate the joint admission control and discrete-phase multicast beamforming design for integrated sensing and commmunications (ISAC) systems, where sensing and communications functionalities have different hierarchies. Specifically, the ISAC system first allocates resources to the higher-hierarchy functionality and opportunistically uses the remaining resources to support the lower-hierarchy one. This resource allocation problem is a nonconvex mixed-integer nonlinear program (MINLP). We propose an exact mixed-integer linear program (MILP) reformulation, leading to a globally optimal solution. In addition, we implemented three baselines for comparison, which our proposed method outperforms by more than 39%.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-11-26
DOI
https://doi.org/10.1109/lcomm.2024.3506696
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Hierarchical Functionality Prioritization in Multicast ISAC: Optimal Admission Control and Discrete-Phase Beamforming

Luis F. Abanto‐Leon, Setareh Maghsudi
IEEE Communications Letters
Advanced Wireless Network Optimization
article

Hierarchical Functionality Prioritization in Multicast ISAC: Optimal Admission Control and Discrete-Phase Beamforming

Luis F. Abanto‐Leon, Setareh Maghsudi
article en

Abstract

We investigate the joint admission control and discrete-phase multicast beamforming design for integrated sensing and commmunications (ISAC) systems, where sensing and communications functionalities have different hierarchies. Specifically, the ISAC system first allocates resources to the higher-hierarchy functionality and opportunistically uses the remaining resources to support the lower-hierarchy one. This resource allocation problem is a nonconvex mixed-integer nonlinear program (MINLP). We propose an exact mixed-integer linear program (MILP) reformulation, leading to a globally optimal solution. In addition, we implemented three baselines for comparison, which our proposed method outperforms by more than 39%.

IEEE Communications LettersVol. 29(1)
Ruhr University Bochum (DE)
Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 81%
Advanced Wireless Network Optimization
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