A GPU implementation for two MIMO-OFDM detectors
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}
}
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.
April 25, 2011 by hgpu
