Hardware Implementation of Temporal Interference Mitigation for Integrated Sensing and Communication Systems
Yang Li, Saquib Siddiqui, Alex Rajan Chiriyath, Andrew Herschfelt, Owen Ma, Daniel W. Bliss · 2024
Spectral convergence is an emerging class of radio frequency (RF) applications that enable better performance and limit spectral congestion by cooperating with nearby devices. With the advent of autonomous vehicles, integrated sensing and communications platforms have become increasingly popular, but introducing these new sensing modalities introduces additional spectral congestion and demands more computational resources. While current deployments have found some success by simply adding more sensing devices and moving to higher carrier frequencies, this approach does not scale and is demonstrably suboptimal. Previous studies demonstrate that when properly co-designed, multifunction radar-communications transceivers can perform better with fewer resources. In this paper, we demonstrate the benefits of a co-designed system by comparing the performance with and without cooperation between radar and communication. We implement a classic interference mitigation approach, called temporal mitigation, to enable efficient joint radar-communications on a Xilinx ZCU102 FPGA evaluation platform. We present the performance results of our hardware design, which are lower utilization and shorter latency compared to the software process.