Adaptive Parallel and Iterative QRDM Detection Algorithms based on the Constellation Set Grouping 


Vol. 35,  No. 2, pp. 112-120, Feb.  2010


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  Abstract

In this paper, we propose semi-ML adaptive parallel QRDM (APQRDM) and iterative QRDM (AIQRDM) algorithms based on set grouping. Using the set grouping, the tree-search stage of QRDM algorithm is divided into partial detection phases (PDP). Therefore, when the treesearch stage of QRDM is divided into 4 PDPs, the APQRDM latency is one fourth of that of the QRDM, and the hardware requirements of AIQRDM is approximately one fourth of that of QRDM. Moreover, simulation results show that in 4 × 4 system and at Eb/N0 of 12 dB, APQRDM decreases the average computational complexity to approximately 43% of that of the conventional QRDM. Also, at Eb/N0 of 0dB, AIQRDM reduces the computational complexity to about 54% and the average number of metric comparisons to approximately 10% of those required by the conventional QRDM and AQRDM.

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  Cite this article

[IEEE Style]

M. Mohaisen, H. An, K. Chang, B. Koo, Y. Baek, "Adaptive Parallel and Iterative QRDM Detection Algorithms based on the Constellation Set Grouping," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 2, pp. 112-120, 2010. DOI: .

[ACM Style]

Manar Mohaisen, HongSun An, KyungHi Chang, BonTae Koo, and Young-Seok Baek. 2010. Adaptive Parallel and Iterative QRDM Detection Algorithms based on the Constellation Set Grouping. The Journal of Korean Institute of Communications and Information Sciences, 35, 2, (2010), 112-120. DOI: .

[KICS Style]

Manar Mohaisen, HongSun An, KyungHi Chang, BonTae Koo, Young-Seok Baek, "Adaptive Parallel and Iterative QRDM Detection Algorithms based on the Constellation Set Grouping," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 2, pp. 112-120, 2. 2010.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880