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Integrated sensing and communication based on space-time-coding metasurfaces
This study proposes an integrated sensing and communication (ISAC) scheme leveraging space-timecoding metasurfaces (STCMs), which enables concurrent wireless communication and sensing on a shared platform.
Conversely, when the STCM is operational, the demodulated constellation diagrams consistently exhibit good quality, and the EVM and BER are maintained at low levels, thus facilitating a satisfactory reconstruction of the transmitted image irrespective of the position of antenna ANT1. We have proposed two coding strategies based on the STCM technology and, with the aid of experiments, we have demonstrated their capability of precisely and flexibly shaping the fundamental-frequency wave and estimating the DOA, and dynamically adjusting the power allocation between the communication and sensing. This model is trained and optimized using TensorFlow 71 on a desktop computer equipped with an NVIDIA Quadro RTX 8000 Graphical Processing Unit (GPU), and an AMD Ryzen Threadripper 3970 × 32-Core Processor @3.69 GHz, and 256 GB of RAM, operating on Windows 10 (Microsoft).
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