2012 IEEE International Symposium on Circuits and Systems 2012
DOI: 10.1109/iscas.2012.6271909
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Sorted QR decomposition for high-speed MMSE MIMO detection based wireless communication systems

Abstract: In this paper, we propose a hardware architecture of high-speed sorted QR decomposition for a 4x4 MMSE MIMO decoder. A QR decomposition (QRD) is commonly used in many MIMO detection algorithms. In particular, a sorted QR decomposition (SQRD) is a advanced algorithm to improve a MIMO detection performance. The proposed architecture can decompose an augmented channel matrix for MMSE detection by using modified Gram-Schmidt algorithm with pipelining and resource sharing processing. This architecture can be applie… Show more

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Cited by 18 publications
(22 citation statements)
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“…QRD of a matrix can be implemented efficiently using different algorithms, such as Givens rotation [10], Householder [11], Gram-Schmidt [12], by exploiting the intricate mechanisms of each of these algorithms. However, the computation involved is expensive and has to be performed for each sub-carrier.…”
Section: B Channel Pre-processing-qrdmentioning
confidence: 99%
See 2 more Smart Citations
“…QRD of a matrix can be implemented efficiently using different algorithms, such as Givens rotation [10], Householder [11], Gram-Schmidt [12], by exploiting the intricate mechanisms of each of these algorithms. However, the computation involved is expensive and has to be performed for each sub-carrier.…”
Section: B Channel Pre-processing-qrdmentioning
confidence: 99%
“…HYBRID SQRD UPDATE ALGORITHM SQRD is capable of improving detection performance by optimizing processing order based on energy of spatial channels. SQRD starts with a column permutation of the original channel matrix , (12) where and denote the sorted channel and the permutation matrix, respectively. The optimal sorting strives to achieve , for , which can be computed using an iterative sorting Gram-Schmidt algorithm [7].…”
Section: B Channel Pre-processing-qrdmentioning
confidence: 99%
See 1 more Smart Citation
“…HT method [12], [13] has a good adaptability even for decomposing correlated matrices, but relatively high complexity makes HT method unfavorable for hardware implementation. GS method [14], [15] is notable for its low latency because it decomposes matrices at columnwise. However, as GS method entails plenty of multipliers and other complicated operations such as square root and division, its hardware overhead is relatively higher.…”
Section: Introductionmentioning
confidence: 99%
“…Patel [6] Huang [5] Miyaoka [7] This Work is defined as the ratio of normalized throughput over the gate count [5]. The energy consumption is calculated as the ratio of normalized power over the throughput.…”
mentioning
confidence: 99%