Highly parallel decoding of space-time codes on graphics processing units

Authors:
Kalyana C. Bollapalli;Yiyue Wu;Kanupriya Gulati;Sunil Khatri;A. Robert Calderbank
Affiliations:
Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX;Department of Electrical Engineering, Princeton University, Princeton, NJ;Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX;Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX;Department of Electrical Engineering, Princeton University, Princeton, NJ
Venue:
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Year:
2009

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Abstract

Graphics Processing Units (GPUs) with a few hundred extremely simple processors represent a paradigm shift for highly parallel computations. We use this emergent GPU architecture to provide a first demonstration of the feasibility of real time ML decoding (in software) of a high rate space-time block code that is representative of codes incorporated in 4th generation wireless standards such as WiMAX and LTE. The decoding algorithm is conditional optimization which reduces to a parallel calculation that is a natural fit to the architecture of low cost GPUs. Experimental results demonstrate that asymptotically the GPU implementation is more than 700 times faster than a standard serial implementation. These results suggest that GPU architectures have the potential to improve the cost / performance tradeoff of 4th generation wireless base stations. Additional benefits might include reducing the time required for system development and the time required for configuration and testing of wireless base stations.