GPU-based real-time beamforming for large arrays of optical wireless acoustic sensors

Recent optical wireless acoustic sensors have demonstrated the possibility to simultaneously sense massive numbers of audio channels in real time. Although this technology has enabled the deployment of large-scale applications, it raises new challenges from the computational perspective. In this regard, Graphics Processing Units provide significant parallel computational power. However, not all the existent algorithms are GPU-implementable in a straightforward way. This paper discusses signal processing schemes and implementation strategies to achieve real-time broadband beamforming using a single GPU card. The experiments introduced here, show our prototype implementation handling over 120 audio channels in real time. The experimental results further highlight the particular advantages of using a video camera-based approach to improve the beamforming performance.