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Date
2011-01-06Type
- Journal Article
ETH Bibliography
yes
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Abstract
Detection algorithms for multiple-input multiple-output (MIMO) wireless systems based on orthogonal frequency-division multiplexing (OFDM) typically require the computation of a QR decomposition for each of the data-carrying OFDM tones. The resulting computational complexity will, in general, be significant. Motivated by the fact that the channel matrices arising in MIMO-OFDM systems result from oversampling of a polynomial matrix, we formulate interpolation-based QR decomposition algorithms. An in-depth complexity analysis, based on a metric relevant for very large scale integration (VLSI) implementations, shows that the proposed algorithms, for a sufficiently large number of data-carrying tones and sufficiently small channel order, provably exhibit significantly smaller complexity than brute-force per-tone QR decomposition. Show more
Publication status
publishedExternal links
Journal / series
IEEE Transactions on Signal ProcessingVolume
Pages / Article No.
Publisher
IEEESubject
Matrix decomposition; MIMO; Interpolation; Polynomials; Signal processing algorithms; OFDM; Very large scale integrationOrganisational unit
03610 - Boelcskei, Helmut / Boelcskei, Helmut
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ETH Bibliography
yes
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