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Unified bit-based probabilistic data association aided MIMO detection for high-order QAM constellations

Yang, Shaoshi, Lv, Tiejun, Maunder, Robert G. and Hanzo, Lajos (2011) Unified bit-based probabilistic data association aided MIMO detection for high-order QAM constellations IEEE Transactions on Vehicular Technology, 60, (3), pp. 981-991. (doi:10.1109/TVT.2011.2114376).

Record type: Article


A unified Bit-based Probabilistic Data Association (B-PDA) detection approach is proposed for Multiple-Input Multiple-Output (MIMO) systems employing high-order rectangular Quadrature Amplitude Modulation (QAM). The new approach transforms the symbol detection process of QAM to a bit-based process by introducing a Unified Matrix Representation (UMR) of QAM. Both linear natural and nonlinear binary reflected Gray bit-to-symbol mappings are considered. With the aid of simulation results, we demonstrate that the linear natural mapping based B-PDA approach typically attained an improved detection performance (measured in terms of both Bit Error Ratio (BER) and Symbol Error Ratio (SER)) in comparison to the conventional symbol-based PDA aided MIMO detector, despite its dramatically reduced computational complexity. The only exception is that at low SNRs, the linear natural mapping based B-PDA is slightly inferior in terms of its BER to the conventional symbol-based PDA using binary reflected Gray mapping. Furthermore, the simulation results show that the linear natural mapping based B-PDA MIMO detector may approach the best-case performance provided by the nonlinear binary reflected Gray mapping based B-PDA MIMO detector under ideal conditions. Additionally, the implementation of the B-PDA MIMO detector is shown to be much simpler in the case of the linear natural mapping. Based on these two points, we conclude that in the context of the uncoded B-PDA MIMO detector it is preferable to use the linear natural bit-to-symbol mapping, rather than the nonlinear Gray mapping.

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Published date: 21 March 2011
Keywords: probabilistic data association, pda, unified matrix representation, umr, high-order qam, low complexity, vector detection
Organisations: Southampton Wireless Group


Local EPrints ID: 271989
ISSN: 0018-9545
PURE UUID: 306ea9d2-a8cd-412f-ba98-14436b7be8c6
ORCID for Robert G. Maunder: ORCID iD

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Date deposited: 07 Feb 2011 15:52
Last modified: 18 Jul 2017 06:36

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Author: Shaoshi Yang
Author: Tiejun Lv
Author: Robert G. Maunder ORCID iD
Author: Lajos Hanzo

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