A GPU implementation for two MIMO-OFDM detectors

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.