Efficient Transceiver Design for MIMO Dual-Function Radar-Communication Systems

This paper considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system. The proposed approach incorporates the design of the (complex-valued) communication receiving (Rx) coefficients, in add...

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Published inIEEE transactions on signal processing Vol. 71; pp. 1 - 16
Main Authors Wen, Cai, Huang, Yan, Davidson, Timothy N.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Approximation
Communication
Communications systems
Complexity
Dual-function radar-communication (DRFC)
integrated sensing and communications (ISAC)
Interference
local approximation refinement
MIMO communication
MIMO radar
MU-MISO communication
Optimization
Precoding
Radar
Sensors
Signal processing algorithms
Signal to noise ratio
successive convex approximation
transceiver design
Transceivers
Waveforms
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Abstract This paper considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system. The proposed approach incorporates the design of the (complex-valued) communication receiving (Rx) coefficients, in addition to the radar Rx filters. We address the problem of maximizing the minimum radar signal-to-interference-plus-noise ratio (SINR) subject to communication SINR, per-antenna power and peak-to-average-power ratio (PAPR) constraints. A successive convex approximation (SCA) algorithm is developed to find a good solution for the resultant nonconvex design problem. To accelerate that algorithm and to improve the solution quality, we further propose a local-approximation-refinement SCA (LAR- SCA) algorithm which possesses guaranteed convergence properties. In addition, a sub-block design technique is developed to reduce the design complexity in the case of long Tx sequences. Numerical results show that by incorporating the communication Rx coefficients into the joint design, the radar and communication capabilities of the DFRC system can be significantly enhanced over the state-of-the-art designs, while maintaining an efficient algorithm.
AbstractList This paper considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system. The proposed approach incorporates the design of the (complex-valued) communication receiving (Rx) coefficients, in addition to the radar Rx filters. We address the problem of maximizing the minimum radar signal-to-interference-plus-noise ratio (SINR) subject to communication SINR, per-antenna power and peak-to-average-power ratio (PAPR) constraints. A successive convex approximation (SCA) algorithm is developed to find a good solution for the resultant nonconvex design problem. To accelerate that algorithm and to improve the solution quality, we further propose a local-approximation-refinement SCA (LAR- SCA) algorithm which possesses guaranteed convergence properties. In addition, a sub-block design technique is developed to reduce the design complexity in the case of long Tx sequences. Numerical results show that by incorporating the communication Rx coefficients into the joint design, the radar and communication capabilities of the DFRC system can be significantly enhanced over the state-of-the-art designs, while maintaining an efficient algorithm.
This article considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system. The proposed approach incorporates the design of the (complex-valued) communication receiving (Rx) coefficients, in addition to the radar Rx filters. We address the problem of maximizing the minimum radar signal-to-interference-plus-noise ratio (SINR) subject to communication SINR, per-antenna power and peak-to-average-power ratio (PAPR) constraints. A successive convex approximation (SCA) algorithm is developed to find a good solution for the resultant nonconvex design problem. To accelerate that algorithm and to improve the solution quality, we further propose a local-approximation-refinement SCA (LAR-SCA) algorithm which possesses guaranteed convergence properties. In addition, a sub-block design technique is developed to reduce the design complexity in the case of long Tx sequences. Numerical results show that by incorporating the communication Rx coefficients into the joint design, the radar and communication capabilities of the DFRC system can be significantly enhanced over the state-of-the-art designs, while maintaining an efficient algorithm.
Author Huang, Yan
Davidson, Timothy N.
Wen, Cai
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Snippet This paper considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function...
This article considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function...
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SubjectTerms Algorithms
Approximation
Communication
Communications systems
Complexity
Dual-function radar-communication (DRFC)
integrated sensing and communications (ISAC)
Interference
local approximation refinement
MIMO communication
MIMO radar
MU-MISO communication
Optimization
Precoding
Radar
Sensors
Signal processing algorithms
Signal to noise ratio
successive convex approximation
transceiver design
Transceivers
Waveforms
Title Efficient Transceiver Design for MIMO Dual-Function Radar-Communication Systems
URI https://ieeexplore.ieee.org/document/10124714
https://www.proquest.com/docview/2821068899
Volume 71
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