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Proceedings Paper

Rapid prototyping and evaluation of programmable SIMD SDR processors in LISA
Author(s): Ting Chen; Hengzhu Liu; Botao Zhang; Dongpei Liu
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Paper Abstract

With the development of international wireless communication standards, there is an increase in computational requirement for baseband signal processors. Time-to-market pressure makes it impossible to completely redesign new processors for the evolving standards. Due to its high flexibility and low power, software defined radio (SDR) digital signal processors have been proposed as promising technology to replace traditional ASIC and FPGA fashions. In addition, there are large numbers of parallel data processed in computation-intensive functions, which fosters the development of single instruction multiple data (SIMD) architecture in SDR platform. So a new way must be found to prototype the SDR processors efficiently. In this paper we present a bit-and-cycle accurate model of programmable SIMD SDR processors in a machine description language LISA. LISA is a language for instruction set architecture which can gain rapid model at architectural level. In order to evaluate the availability of our proposed processor, three common baseband functions, FFT, FIR digital filter and matrix multiplication have been mapped on the SDR platform. Analytical results showed that the SDR processor achieved the maximum of 47.1% performance boost relative to the opponent processor.

Paper Details

Date Published: 13 March 2013
PDF: 7 pages
Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87841D (13 March 2013); doi: 10.1117/12.2014028
Show Author Affiliations
Ting Chen, National Univ. of Defense Technology (China)
Hengzhu Liu, National Univ. of Defense Technology (China)
Botao Zhang, National Univ. of Defense Technology (China)
Dongpei Liu, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 8784:
Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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