Bit-Interleaved Coded Modulation
Foundations and Trends in Communications and Information Theory
Multidimensional 16-QAM labeling of BI-STCM-ID over 2x2 MIMO channel
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Achieving close-capacity performance with simple concatenation scheme on multiple-antenna channels
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Sphere packing optimization and EXIT chart analysis for multi-dimensional QAM signaling
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
A simple near-capacity bandwidth-efficient coded modulation scheme in rayleigh fading
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Achieving near-capacity performance on multiple-antenna channels with a simple concatenation scheme
IEEE Transactions on Communications
Labeling optimization of differential unitary space-time modulation
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
On the suitability of gray bit mappings to outer channel codes in iteratively decoded BICM
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
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Multidimensional binary mappings for bit-interleaved coded modulations (BICMs) on ergodic multiple-antenna channels with iterative decoding are presented. After derivation of a closed-form expression for the pairwise error probability under ideal maximum-likelihood (ML) decoding, the design criterion for mapping optimization is established from the ML performance of the ideally interleaved channel. It coincides with the figure of merit derived from the genie condition when the iterative receiver converges to perfect a priori information. Multidimensional mapping constructions that exhibit high signal-to-noise ratio (SNR) gains without increasing the complexity of the a posteriori probability (APP) detection are proposed. They allow for a reduced decoding complexity as they achieve near turbo code performance with a single convolutional code.