Abstract
Quadrature amplitude modulation (QAM) is widely used in communication systems. The traditional QAM demodulation method was implemented in hardware. This paper proposes a demodulation algorithm using GPU. The GPU algorithm is easier to add new features than hardware implementation and reaches 57x speed up compared with the serial algorithm on CPU. It is shown that the QAM demodulation algorithm gained significant performance increase due to the natural parallism of the GPU, using Compute Unified Device Architecture (CUDA).
Publisher
Trans Tech Publications, Ltd.
Reference10 articles.
1. M. Dillinger, K. Madani and N. Alonistioti, Software Defined Radio: Architectures, Systems and Functions, Wiley&Sons, (2003).
2. NVIDIA CUDA C Programming Guide, Version 3. 2, NVIDIA, (2010).
3. T. Nylanden, J. Janhunen, O. Silven and M. Juntti, A GPU Implementation for two MIMO–OFDM Detectors, International Conference on Embedded Computer Systems (SAMOS), 2010, pp.293-300.
4. S. Anwar and W. Sung, Digital Signal Processing Filtering with GPU, The Institute of Electronics Engineers of Korea, July (2009).
5. X. Wang and B. Shi, GPU Implemention of Fast Gabor Filters, Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS), p.373 – 376, (2010).