Fast Cyclostationary Feature Detection Method Based on CUDA. Issue 1 (July 2021) - Zhang, Hongyuan; Guo, Bin; Zhang, Yiheng; Hu, Yanfei
Abstract: Aiming at the problem of poor real-time performance of cyclostationary feature detection, a fast cyclostationary feature detection algorithm based on the Unified Computing Device Architecture (CUDA) is proposed. This method moves the data processing part to the GPU, and uses the advantages of a large number of GPU stream processors and powerful multi-threaded concurrent execution functions to accelerate the FAM algorithm in parallel, thereby realizing fast signal processing. Experimental results show that compared with traditional serial algorithms, this method reduces the time overhead of the algorithm and improves the real-time performance of the algorithm.