GPU-based acceleration of symbol timing recovery

This paper presents a novel implementation of graphics processing unit (GPU) based symbol timing recovery using polyphase interpolators to detect symbol timing error. Sym-bol timing recovery is a compute intensive procedure that de-tects and corrects the timing error in a coherent receiver. We provide optimal sample-time timing recovery using a maxi-mum likelihood (ML) estimator to minimize the timing er-ror. This is an iterative and adaptive system that relies on feedback, therefore, we present an accelerated implementa-tion design by using a GPU for timing error detection (TED), enabling fast error detection by exploiting the 2D filter struc-ture found in the polyphase interpolator. We present this hy-brid/heterogeneous CPU and GPU architecture by computing a low complexity and low noise matched filter (MF) while simultaneously performing TED. We then compare the per-formance of the CPU vs. GPU based timing recovery for dif-ferent interpolation rates to minimize the error and improve the detection by up to a factor of 35. We further improve the process by utilizing GPU optimization and performing block processing to improve the throughput even more, all while maintaining the lowest possible sampling rate. Index Terms — GPU, symbol timing recovery, synchro-nization, coherent receiver design, DSP accelerator. 1