3711

A GPU implementation for two MIMO-OFDM detectors

Teemu Nylanden, Janne Janhunen, Olli Silven, Markku J. Juntti
Comput. Sci. & Eng. Lab., Univ. of Oulu, Oulu, Finland
International Conference on Embedded Computer Systems (SAMOS), 2010

@conference{nylanden2010gpu,

   title={A GPU implementation for two MIMO-OFDM detectors},

   author={Nylanden, T. and Janhunen, J. and Silven, O. and Juntti, M.},

   booktitle={Embedded Computer Systems (SAMOS), 2010 International Conference on},

   pages={293–300},

   organization={IEEE}

}

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Two real-valued signal models based on selective spanning with fast enumeration (SSFE) and layered orthogonal lattice detector (LORD) algorithms are implemented on a Nvidia graphics processing unit (GPU). A 2×2 multiple-input multiple-output (MIMO) antenna system with 16-quadrature amplitude modulation (16-QAM) is assumed. The chosen level update vector for SSFE is based on computer simulation results carried out in MATLAB environment. We implemented the algorithms with Nvidia Quadro FX 1700 GPU and achieved a throughput of 36.06 Mbps for SSFE and 16.8 Mbps for LORD. The results show that the general-purpose graphics processing unit (GPGPU) has the potential to achieve high throughput, presuming a detection algorithm that allows efficient parallel processing. The latency of the control code and partial Euclidean distance (PED) calculations are very small-scale, but the latency of memory loads and stores to the GPUs global memory are significant. We also compare results from the trellis based detector implementation for GPU, where a more powerful GPU and a different detection algorithm are used. The GPUs offer superior computing power and programmability compared to the application specific software defined radio (SDR) designs implemented so far.
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