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Complexity Reduction of Matrix Manipulation for Multi-User STBC-MIMO Decoding
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för systemteknik, Datorteknik.
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för systemteknik, Datorteknik.
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för systemteknik, Datorteknik.
Vise andre og tillknytning
2007 (engelsk)Inngår i: IEEE Sarnoff Symmposium,2007, 2007, s. 1-5Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper studies efficient complex valued matrix manipulations for multi-user STBC-MIMO decoding. A novel method called Alamouti blockwise analytical matrix inversion (ABAMI) is proposed for the inversion of large complex matrices that are based on Alamouti sub-blocks. Another method using a variant of Givens rotation is proposed for fast QR decomposition of this kind of matrices. Our solutions significantly reduce the number of operations which makes them more than 4 times faster than several other solutions in the literature. Furthermore, compared to fixed function VLSI implementations, our solution is more flexible and consumes less silicon area because the hardware is programmable and it can be reused for many other operations such as filtering, correlation and FFT/IFFT. Besides the analysis of the general computational complexity based on the number of basic operations, the computational latency is also measured in clock cycles based on the conceptual hardware for real-time matrix manipulations.

sted, utgiver, år, opplag, sider
2007. s. 1-5
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-39861DOI: 10.1109/SARNOF.2007.4567354Lokal ID: 51543ISBN: 978-1-4244-2483-2 (tryckt)OAI: oai:DiVA.org:liu-39861DiVA, id: diva2:260710
Konferanse
Sarnoff Symposium, April 30-May 2, Nassau Inn, Princeton, NJ, USA
Tilgjengelig fra: 2009-10-10 Laget: 2009-10-10 Sist oppdatert: 2011-02-04
Inngår i avhandling
1. ASIP for Wireless Communication and Media
Åpne denne publikasjonen i ny fane eller vindu >>ASIP for Wireless Communication and Media
2010 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

While general purpose processors reach both high performance and high application flexibility, this comes at a high cost in terms of silicon area and power consumption. In systems where high application flexibility is not required, it is possible to trade off flexibility for lower cost by tailoring the processor to the application to create an Application Specific Instruction set Processor (ASIP) with high performance yet low silicon cost.

This thesis demonstrates how ASIPs with application specific data types can provide efficient solutions with lower cost. Two examples are presented, an audio decoder ASIP for audio and music processing and a matrix manipulation ASIP for MIMO radio baseband signal processing.

The audio decoder ASIP uses a 16-bit floating point data type to reduce the size of the data memory to about 60% of other solutions that use a 32-bit data type. Since the data memory occupies a major part of the silicon area, this has a significant impact on the total silicon area, and thereby also the static and dynamic power consumption. The data width reduction can be done without any noticeable artifacts in the decoded audio due to the natural masking effect ofthe human ear.

The matrix manipulation SIMD ASIP is designed to perform various matrix operations such as matrix inversion and QR decomposition of small complex-valued matrices. This type of processing is found in MIMO radio baseband signal processing and the matrices are typically not larger than 4x4. There have been solutions published that use arrays of fixed-function processing elements to perform these operations, but the proposed ASIP performs the computations in less time and with lower hardware cost.

The matrix manipulation ASIP data path uses a floating point data type to avoid data scaling issues associated with fixed point computations, especially those related to division and reciprocal calculations, and it also simplifies the program control flow since no special cases for certain inputs are needed which is especially important for SIMD architectures.

These two applications were chosen to show how ASIPs can be a suitable alternative and match the requirements for different types of applications, to provide enough flexibility and performance to support different standards and algorithms with low hardware cost.

sted, utgiver, år, opplag, sider
Linköping: Linköping University Electronic Press, 2010. s. 43
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1298
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-65355 (URN)978-91-7393-450-3 (ISBN)
Disputas
2010-02-26, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2011-02-04 Laget: 2011-02-04 Sist oppdatert: 2011-02-04bibliografisk kontrollert

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