MIMO-ISAC Precoding Design Toward Random Signals

LIU Fan; LU Shihang; CHEN Zihao

doi:10.12000/JR25019

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LIU Fan, LU Shihang, and CHEN Zihao. MIMO-ISAC precoding design toward random signals[J]. Journal of Radars, in press. doi: 10.12000/JR25019

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LIU Fan, LU Shihang, and CHEN Zihao. MIMO-ISAC precoding design toward random signals[J]. Journal of Radars, in press. doi: 10.12000/JR25019

LIU Fan, LU Shihang, and CHEN Zihao. MIMO-ISAC precoding design toward random signals[J]. Journal of Radars, in press. doi: 10.12000/JR25019

Citation:

LIU Fan, LU Shihang, and CHEN Zihao. MIMO-ISAC precoding design toward random signals[J]. Journal of Radars, in press. doi: 10.12000/JR25019

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MIMO-ISAC Precoding Design Toward Random Signals

DOI: 10.12000/JR25019 CSTR: 32380.14.JR25019

LIU Fan¹,
LU Shihang^{2
,
,},
CHEN Zihao²

1.
National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
2.
School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen 518055, China

Funds: Guangdong Basic and Applied Basic Research Foundation under Grant (2024A1515011218)

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Corresponding author: LU Shihang, lush2021@mail.sustech.edu.cn
Received Date: 2025-01-22
Rev Recd Date: 2025-03-15

Available Online: 2025-03-20

Abstract

Abstract

Integrated Sensing And Communications (ISAC) based on reusing random communication signals within the existing network architecture may drastically reduce implementation costs, thereby accelerating the integration of sensing functionalities into current communication networks. However, the randomness of communication data introduces fluctuations in sensing performance across different signal realizations, leading to unstable sensing accuracy. To address this issue, we delve into random ISAC signal processing methods and propose a joint transceiver precoding optimization design for Multiple-Input Multiple-Output ISAC (MIMO-ISAC) systems. Specifically, considering target impulse response matrix estimation, we first define the Ergodic Cramér–Rao Bound (ECRB) as an average sensing performance metric under random signaling. By deriving the closed-form expression of the ECRB based on the distribution of complex inverse Wishart matrices, we theoretically reveal the performance loss arising when using random signals for sensing compared to the conventional deterministic orthogonal signals. Furthermore, we formulate the sensing-optimal subproblem by minimizing the ECRB and the communication-optimal subproblem of multiantenna multiuser signal estimation and derive the corresponding sensing-optimal and communication-optimal precoding designs. Subsequently, we extend the proposed transceiver precoding optimization framework to ISAC scenarios by explicitly constraining the communication requirements. Finally, through numerous simulations, we validate the effectiveness of the proposed method. The results demonstrate that the joint transceiver precoding design may allow high-accuracy target response matrix estimation while enabling flexible trade-offs between communication signal estimation and target response matrix estimation errors.
- Integrated sensing and communications,
- Multiple-input multiple-output systems,
- Precoding designs,
- Signal processing,
- Multiple-user communications

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