Parallel Multitarget Sensing and Echo Separation in MmWave Integrated Sensing and Communication Systems

Le résumé fourni par la source

The design of the dual-function signal is critical to integrated sensing and communication (ISAC). The communication and sensing signals share the channel estimation techniques since both communication and sensing capabilities rely on channel state information (CSI). A communication system typically estimate channels with specific preambles can be reused for sensing, which facilitates the integration of sensing with communication. With augmented sensing capability within existing communication frameworks, the ISAC systems based on preamble sharing achieves improved spectral efficiency and reduced costs. However, in multi-target scenarios, echoes from different targets cannot be accurately distinguished at the receiver, leading to severe sensing ambiguity. To address this issue, we propose a PArallel Multi-target Sensing and Echo Separation (PAMSES) scheme for ISAC systems operating in multi-user and multi-target environments. The receiver exploits the waveform diversity to discriminate echoes from distinct targets, effectively resolving multi-target sensing ambiguity. Furthermore, since perfect CSI is usually unavailable at the access point, we formulate a robust optimization problem to ensure reliable communication and sensing performance in the worst-case scenario. The proposed problem can be formulated as a semidefinite program (SDP) and solved through semidefinite relaxation (SDR) techniques. Simulation results demonstrate that the proposed method can achieve 0.01 m/s velocity estimation accuracy and 5 bps/Hz spectrum efficiency, while maintaining an energy efficiency of 6.27 bit/J/Hz.

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