Forward error correction with RaptorQ code on GPU

RaptorQ code, the next generation of Raptor code for forward error correction (FEC), is proposed to significantly reduce the redundant information. However, the improved coding performance comes at the expense of increased encoding and decoding complexity. On the other hand, graphics processing units (GPUs) are finding their way beyond graphics processing into general purpose computing in the consumer market. This paper investigates the suitability of GPU for RaptorQ code to process large block and symbol sizes in FEC transmission. The paper explores serial and parallel implementations of Raptor code on CPU and GPU, respectively. Our work shows that efficient parallelization on the GPU can improve the performance of the decoder significantly. Furthermore, simulations are performed for the practical real time requirement in multimedia broadcast/multicast service (MBMS) and digital video broadcasting (DVB) in highspeed downlink packet access (HSDPA) network. Conclusions are drawn with respect to the applicability of this new code for realtime multimedia broadcasting and content delivery on GPU.