Algorithms for interpolation-based QR decomposition in MIMO-OFDM systems


Davide Cescato and Helmut Bölcskei


IEEE Transactions on Signal Processing, Vol. 59, No. 4, pp. 1719-1733, Apr. 2011.

DOI: 10.1109/TSP.2010.2104149

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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.


Interpolation, polynomial matrices, multiple-input multiple-output (MIMO) systems, orthogonal frequency-division multiplexing (OFDM), QR decomposition, sphere decoding, successive cancelation, very large scale integration (VLSI)

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