A GPU implementation of a real-time MIMO detector

Michael Wu, Siddharth Gupta, Yang Sun, Joseph R. Cavallaro
Electrical and Computer Engineering, Rice University, Houston, Texas 77005, USA
IEEE Workshop on Signal Processing Systems, 2009. SiPS 2009


   title={A GPU implementation of a real-time MIMO detector},

   author={Wu, M. and Gupta, S. and Sun, Y. and Cavallaro, J.R.},

   booktitle={Signal Processing Systems, 2009. SiPS 2009. IEEE Workshop on},






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Multiple-input multiple-output (MIMO) is an existing technique that can significantly increase throughput of the system by employing multiple antennas at the transmitter and the receiver. Realizing maximum benefit from this technique requires computationally intensive detectors which poses significant challenges to receiver design. Furthermore, a flexible detector or multiple detectors are needed to handle different configurations. Graphical processor unit (GPU), a highly parallel commodity programmable co-processor, can deliver extremely high computation throughput and is well suited for signal processing applications. However, careful architecture aware design is needed to leverage performance offered by GPU. We show we can achieve good performance while maintaining flexibility by employing an optimized trellis-based MIMO detector on GPU.
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