Efficient maximum-likelihood decoding of spherical lattice space-time codes
Karen Su,I. Berenguer,Ian J. Wassell,Xiaodong Wang +3 more
- 11 Dec 2006
- Vol. 7, pp 3008-3013
TL;DR: This paper develops a framework for the efficient maximum-likelihood decoding of lattice codes and applies it to the spherical Lattice Space-Time (LAST) codes recently put forward by El Gamal et al.
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Abstract: This paper develops a framework for the efficient maximum-likelihood decoding of lattice codes. Specifically we apply it to the spherical Lattice Space-Time (LAST) codes recently put forward by El Gamal et al. that have been proven to achieve the optimal diversity-multiplexing tradeoff of MIMO channels. Our solution addresses the so-called boundary control problem within the same search tree structure as existing suboptimal LAST decoders. We demonstrate its performance and complexity by applying two of the most efficient tree-based ML detectors currently reported in the literature to the spherical LAST code proposed for the 2 × 2 MIMO channel of block length 2. Our optimal decoders exhibit improved performance over the naive lattice decoder with MMSE-GDFE pre-processing at a comparable complexity.
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Citations
Coding-Assisted Blind MIMO Separation and Decoding
Xu Zhao,Michael Davies +1 more
TL;DR: Experiments show improvements that are achievable by exploiting the existence of coding structures and that the iterative channel estimation based on a posteriori information for blind MIMO separation and decoding can approach the performance of a Bahl-Cocke-Jelinek-Raviv equalizer with perfect channel-state information in a reasonable signal-to-noise ratio (SNR) range.
A best-first tree-searching approach for ML decoding in MIMO system
Chung-An Shen,Ahmed M. Eltawil,S. Mondal,Khaled N. Salama +3 more
- 03 Aug 2010
TL;DR: It is demonstrated that with a proper choice of storage size the proposed method visits 40% fewer nodes than a sphere decoding algorithm at signal to noise ratio (SNR) = 20dB and by an order of magnitude at 0 dB SNR.
Efficient maximum-likelihood decoding of spherical lattice space-time codes
Karen Su,I. Berenguer,Ian J. Wassell,Xiaodong Wang +3 more
- 11 Dec 2006
TL;DR: This paper develops a framework for the efficient maximum-likelihood decoding of lattice codes and applies it to the spherical Lattice Space-Time (LAST) codes recently put forward by El Gamal et al.
Design of Spherical Lattice Space–Time Codes
TL;DR: A systematic procedure for designing spherical lattice (space-time) codes by employing stochastic optimization techniques and obtaining fundamental lower bounds on the error probabilities yielded by lattice and LRA decoders and characterize their asymptotic behavior.
2
Coding assisted blind MIMO equalization and decoding
Xu Zhao,Michael Davies +1 more
- 24 Aug 2009
TL;DR: This work exploits the iterative channel estimation and decoding performance for blind MIMO equalization to improve blind multiple input multiple output (MIMO) channel estimates.
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Babak Hassibi,Haris Vikalo +1 more
TL;DR: For the "sphere decoding" algorithm of Fincke and Pohst, a closed-form expression is found for the expected complexity, both for the infinite and finite lattice, which suggests that maximum-likelihood decoding, which was hitherto thought to be computationally intractable, can be implemented in real time.