Digital signal processor against field programmable gate array implementations of space–code correlator beamformer for smart antennas

Software radio implementations of beamformers on programmable processors such as digital signal processor (DSP) and field programmable gate array (FPGA) still remain as a challenge for the integration of smart antennas into existing wireless base stations for 3G systems. This study presents the comp...

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Bibliographic Details
Published in:IET microwaves, antennas & propagation Vol. 4; no. 5; pp. 593 - 599
Main Authors: Dikmese, S., Kavak, A., Kucuk, K., Sahin, S., Tangel, A., Dincer, H.
Format: Journal Article
Language:English
Published: Stevenage The Institution of Engineering & Technology 01.05.2010
Subjects:
Antennas
Beamforming
Digital
Digital signal processing
Field programmable gate arrays
Floating point arithmetic
Microprocessors
Signal processing
ISSN:1751-8725, 1751-8733
Online Access:Get full text
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Summary:Software radio implementations of beamformers on programmable processors such as digital signal processor (DSP) and field programmable gate array (FPGA) still remain as a challenge for the integration of smart antennas into existing wireless base stations for 3G systems. This study presents the comparison of DSP- and FPGA-based implementations of space-code correlator (SCC) beamformer, which is practical to use in CDMA2000 systems. Implementation methodology is demonstrated and results regarding beamforming accuracy, weight vector computation time and resource utilisation are presented. The SCC algorithm is implemented on Texas Instruments TMS320C6713 floating-point digital signal processors (DSP) and Xilinx's VirtexIV family FPGA. In signal modelling, CDMA2000 reverse link format is employed. The results show that beamformer weights can be obtained within less than 10 ms via implementation on c6713 DSP with direction-of-arrival search resolution of Δθ = 2 degrees, whereas it can be achieved within less than 25 μs on VirtexIV FPGA for five-element uniform linear array.
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ISSN:1751-8725
1751-8733
DOI:10.1049/iet-map.2009.0151