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1. CRB Optimization for Joint Array Partitioning and Beamforming Design in ISAC Systems

   https://doi.org/10.1109/IEEECONF60004.2024.10942840  

   Liu, Rang; Swindlehurst, A Lee; Li, Ming (October 2024, IEEE)

   Integrated sensing and communication has emerged as a transformative technology for future wireless communication networks, enabling the simultaneous realization of radar sensing and communication functions by sharing available resources. To fully exploit the available spatial degrees of freedom in monostatic ISAC systems, we propose a dynamic array partitioning architecture that allows the base station to allocate antennas for transmitting dual-functional signals and receiving the corresponding echoes. Based on this architecture, we jointly design the transmit beamforming and array partitioning to minimize the Cram´er-Rao bound (CRB) for target directionof- arrival estimation, while ensuring compliance with signalto- interference-plus-noise ratio requirements for multiuser communication, power budget constraints, and array partitioning limitations. To address the resulting optimization problem, we develop an alternating algorithm leveraging alternating direction method of multipliers and semi-definite relaxation. Simulation results demonstrate that the proposed joint array partitioning and beamforming design significantly improves the CRB and the resulting DOA estimation performance. 

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2. SNR/CRB-Constrained Joint Beamforming and Reflection Designs for RIS-ISAC Systems

   https://doi.org/10.1109/TWC.2023.3341429  

   Liu, Rang; Li, Ming; Liu, Qian; Lee_Swindlehurst, A (July 2024, IEEE Transactions on Wireless Communications)

   In this paper, we investigate the integration of integrated sensing and communication (ISAC) and reconfigurable intelligent surfaces (RIS) for providing wide-coverage and ultrareliable communication and high-accuracy sensing functions. In particular, we consider an RIS-assisted ISAC system in which a multi-antenna base station (BS) simultaneously performs multiuser multi-input single-output (MU-MISO) communications and radar sensing with the assistance of an RIS. We focus on both target detection and parameter estimation performance in terms of the signal-to-noise ratio (SNR) and Cramér-Rao bound (CRB), respectively. Two optimization problems are formulated for maximizing the achievable sum-rate of the multi-user communications under an SNR constraint for target detection or a CRB constraint for parameter estimation, the transmit power budget, and the unit-modulus constraint of the RIS reflection coefficients. Efficient algorithms are developed to solve these two complicated non-convex problems. We then extend the proposed joint design algorithms to the scenario with imperfect self-interference cancellation. Extensive simulation results demonstrate the advantages of the proposed joint beamforming and reflection designs compared with other schemes. In addition, it is shown that more RIS reflection elements bring larger performance gains for directof- arrival (DoA) estimation than for target detection. 

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3. Joint Beamforming and Reflection Design for RIS-assisted ISAC Systems

   https://doi.org/10.23919/EUSIPCO55093.2022.9909807  

   Liu, Rang; Li, Ming; Swindlehurst, A. Lee (August 2022, 022 30th European Signal Processing Conference (EUSIPCO))

   In this paper, we investigate the potential of employing reconfigurable intelligent surface (RIS) in integrated sensing and communication (ISAC) systems. In particular, we consider an RIS-assisted ISAC system in which a multi-antenna base station (BS) simultaneously performs multi-user multi-input single-output (MU-MISO) communication and target detection. We aim to jointly design the transmit beamforming and receive filter of the BS, and the reflection coefficients of the RIS to maximize the sum-rate of the communication users, while satisfying a worst-case radar output signal-to-noise ratio (SNR), the transmit power constraint, and the unit modulus property of the reflecting coefficients. An efficient iterative algorithm based on fractional programming (FP), majorization-minimization (MM), and alternative direction method of multipliers (ADMM) is developed to solve the complicated non-convex problem. Simulation results verify the advantage of the proposed RIS-assisted ISAC scheme and the effectiveness of the developed algorithm. 

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4. Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity

   https://doi.org/10.1109/GlobalSIP45357.2019.8969105  

   Lee, Gary C.; Rawat, Ankit S.; Wornell, Gregory W. (November 2019, IEEE Global Conference on Signal and Information Processing (GlobalSIP))

   Many direction-of-arrival (DOA) estimation algo- rithms require accurate measurements from all sensing elements on an antenna array. However, in various practical settings, it becomes imperative to perform DOA estimation even in the presence of faulty elements. In this work, we develop an algorithm that can jointly estimate the DOA of sources and the locations of the faulty elements. This is achieved by introducing weights that describe the degree of outlierness of each element. Further, for situations where only single snapshots are available, we propose a new snapshot diversity formulation for which our algorithm can still be applied. Simulation results over four different fault models demonstrate that the proposed algorithm robustly estimates DOAs and accurately identifies the faulty elements. 

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5. Implementation of the Digital QS-SVM-Based Beamformer on an FPGA Platform

   https://doi.org/10.3390/s23031742  

   Komeylian, Somayeh; Paolini, Christopher (February 2023, Sensors)

   To address practical challenges in establishing and maintaining robust wireless connectivity such as multi-path effects, low latency, size reduction, and high data rate, we have deployed the digital beamformer, as a spatial filter, by using the hybrid antenna array at an operating frequency of 10 GHz. The proposed digital beamformer utilizes a combination of the two well-established beamforming techniques of minimum variance distortionless response (MVDR) and linearly constrained minimum variance (LCMV). In this case, the MVDR beamforming method updates weight vectors on the FPGA board, while the LCMV beamforming technique performs nullsteering in directions of interference signals in the real environment. The most well-established machine learning technique of support vector machine (SVM) for the Direction of Arrival (DoA) estimation is limited to problems with linearly-separable datasets. To overcome the aforementioned constraint, the quadratic surface support vector machine (QS-SVM) classifier with a small regularizer has been used in the proposed beamformer for the DoA estimation in addition to the two beamforming techniques of LCMV and MVDR. In this work, we have assumed that five hybrid array antennas and three sources are available, at which one of the sources transmits the signal of interest. The QS-SVM-based beamformer has been deployed on the FPGA board for spatially filtering two signals from undesired directions and passing only one of the signals from the desired direction. The simulation results have verified the strong performance of the QS-SVM-based beamformer in suppressing interference signals, which are accompanied by placing deep nulls with powers less than −10 dB in directions of interference signals, and transferring the desired signal. Furthermore, we have verified that the performance of the QS-SVM-based beamformer yields other advantages including average latency time in the order of milliseconds, performance efficiency of more than 90%, and throughput of nearly 100%. 

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