Doubly Constrained Waveform Optimization for Integrated Sensing and Communications.

Ni, Z; Zhang, AJ; Liu, R-P; Yang, K

Doubly Constrained Waveform Optimization for Integrated Sensing and Communications.

Ni, Z

Zhang, AJ Liu, R-P Yang, K

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Sensors (Basel), 2023, 23, (13), pp. 5988
Issue Date:: 2023-06-28

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Field	Value	Language
dc.contributor.author	Ni, Z https://orcid.org/0000-0002-7932-5996
dc.contributor.author	Zhang, AJ
dc.contributor.author	Liu, R-P
dc.contributor.author	Yang, K
dc.date.accessioned	2024-03-25T07:20:55Z
dc.date.available	2023-06-21
dc.date.available	2024-03-25T07:20:55Z
dc.date.issued	2023-06-28
dc.identifier.citation	Sensors (Basel), 2023, 23, (13), pp. 5988
dc.identifier.issn	1424-8220
dc.identifier.issn	1424-8220
dc.identifier.uri	http://hdl.handle.net/10453/177111
dc.description.abstract	This paper investigates threshold-constrained joint waveform optimization for an integrated sensing and communication (ISAC) system. Unlike existing studies, we employ mutual information (MI) and sum rate (SR) as sensing and communication metrics, respectively, and optimize the waveform under constraints to both metrics simultaneously. This provides significant flexibility in meeting system performance. We formulate three different optimization problems that constrain the radar performance only, the communication performance only, and the ISAC performance, respectively. New techniques are developed to solve the original problems, which are NP-hard and cannot be directly solved by conventional semi-definite programming (SDP) techniques. Novel gradient descent methods are developed to solve the first two problems. For the third non-convex optimization problem, we transform it into a convex problem and solve it via convex toolboxes. We also disclose the connections between three optimizations using numerical results. Finally, simulation results are provided and validate the proposed optimization solutions.
dc.format	Electronic
dc.language	eng
dc.publisher	MDPI
dc.relation	http://purl.org/au-research/grants/arc/DP210101411
dc.relation.ispartof	Sensors (Basel)
dc.relation.isbasedon	10.3390/s23135988
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0301 Analytical Chemistry, 0502 Environmental Science and Management, 0602 Ecology, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering
dc.subject.classification	Analytical Chemistry
dc.subject.classification	3103 Ecology
dc.subject.classification	4008 Electrical engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4104 Environmental management
dc.subject.classification	4606 Distributed computing and systems software
dc.subject.mesh	Algorithms
dc.subject.mesh	Computer Simulation
dc.subject.mesh	Algorithms
dc.subject.mesh	Computer Simulation
dc.subject.mesh	Algorithms
dc.subject.mesh	Computer Simulation
dc.title	Doubly Constrained Waveform Optimization for Integrated Sensing and Communications.
dc.type	Journal Article
utslib.citation.volume	23
utslib.location.activity	Switzerland
utslib.for	0301 Analytical Chemistry
utslib.for	0502 Environmental Science and Management
utslib.for	0602 Ecology
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	University of Technology Sydney/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	open_access	*
dc.date.updated	2024-03-25T07:20:53Z
pubs.issue	13
pubs.publication-status	Published online
pubs.volume	23
utslib.citation.issue	13

Abstract:

This paper investigates threshold-constrained joint waveform optimization for an integrated sensing and communication (ISAC) system. Unlike existing studies, we employ mutual information (MI) and sum rate (SR) as sensing and communication metrics, respectively, and optimize the waveform under constraints to both metrics simultaneously. This provides significant flexibility in meeting system performance. We formulate three different optimization problems that constrain the radar performance only, the communication performance only, and the ISAC performance, respectively. New techniques are developed to solve the original problems, which are NP-hard and cannot be directly solved by conventional semi-definite programming (SDP) techniques. Novel gradient descent methods are developed to solve the first two problems. For the third non-convex optimization problem, we transform it into a convex problem and solve it via convex toolboxes. We also disclose the connections between three optimizations using numerical results. Finally, simulation results are provided and validate the proposed optimization solutions.

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http://hdl.handle.net/10453/177111