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Qijun Deng
Qijun Deng

Public Documents 2
Joint Beamforming and Reflection Design for IRS-Aided Co-existing Radar and Communica...
Qijun Deng
zhengming jiang

Qijun Deng

and 4 more

August 03, 2024
not-yet-known not-yet-known not-yet-known unknown Optimum performance of co-existing radar and communication (CRC) system is a challenging task when target and user exist within a crowded area where path-loss is dominant. Inspired by the application of intelligent reflecting surface (IRS) in reconstructing the wireless transmission environment, this paper investigates deploying IRS to the CRC system to pursue performance improvement. Particularly, we consider an IRS-assisted CRC system where the IRS not only provides an indirect communication path but inevitably introduces additional interfering paths. Our goal is to maximize the radar signal-to-interference-plus noise ratio (SINR) by jointly optimizing the transmit beamform and the phase of IRS while satisfying the user SINR, the total transmit power at the radar and base station (BS), the restriction of IRS phaseshift. An efficient alternative optimization algorithm combining the second-order cone programming (SOCP) and semidefinite programming (SDP) optimization methods is exploited to solve the complicated non-convex unit-norm problem. Simulation results reveal the advantages of deploying IRS in the CRC system and the effectiveness of our proposed algorithm.
Robust Beamforming Design for Co-existing Radar and Communication System with Bounded...
Qijun Deng
zhengming jiang

Qijun Deng

and 5 more

June 02, 2024
The achievement of optimum performance of a co-existing radar and communication (CRC) system is a challenging task when the channel state information (CSI) for the interference channels is imperfect, particularly when the power of the CRC system is restricted. To address this issue, this article proposes a robust CRC system design that considers CSI uncertainty. Specifically, the objective is to design a robust beamforming scheme to maximize the radar performance subject to the user signal-to-interference-plus-noise ratio (SINR)and the transmit power of the CRC system. Due to the infinite number of constraints that result from the CSI uncertainty of the interference channels, a loosely bound robust approach is developed, which employs the shrinkage method to convert the infinite number of constraints into a finite number of constraints. However, the performance of the loosely bound robust approach is not satisfactory. Therefore, this paper further proposes a sub-optimal robust approach that employs the S-procedure to transform the infinite number of inequality constraints into equivalent finite linear matrix inequalities (LMIs). The simulation results indicate that the design of the robust CRC system can significantly improve the system performance compared to the traditional design approach.

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