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Implementation of a High Throughput Soft MIMO Detector on GPU

Michael Wu, Yang Sun, Siddharth Gupta, Joseph Cavallaro
Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
Journal of Signal Processing Systems (7 September 2010), pp. 1-14-14.

@article{wuimplementation,

   title={Implementation of a High Throughput Soft MIMO Detector on GPU},

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

   journal={Journal of Signal Processing Systems},

   pages={1–14},

   issn={1939-8018},

   publisher={Springer}

}

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Multiple-input multiple-output (MIMO) significantly increases the throughput of a communication system by employing multiple antennas at the transmitter and the receiver. To extract maximum performance from a MIMO system, a computationally intensive search based detector is needed. To meet the challenge of MIMO detection, typical suboptimal MIMO detectors are ASIC or FPGA designs. We aim to show that a MIMO detector on Graphic processor unit (GPU), a low-cost parallel programmable co-processor, can achieve high throughput and can serve as an alternative to ASIC/FPGA designs. However, careful architecture aware software design is needed to leverage the performance offered by GPU. We propose a novel soft MIMO detection algorithm, multi-pass trellis traversal (MTT), and show that we can achieve ASIC/FPGA-like performance and handle different configurations in software on GPU. The proposed design can be used to accelerate wireless physical layer simulations and to offload MIMO detection processing in wireless testbed platforms.
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