Low Complexity Decoding of the 4×4 Perfect Space-time Block Code

Amani, Elie; Djouani, Karim; Kurien, Anish Mathew

doi:10.1016/j.procs.2014.05.418

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…The most immediate task at hand is that of experimental error rates for various algebraic space-time codes, comparing our algorithm with ML-decoding and with the algorithms proposed in [5][6][7]. This simulation results are forthcoming and will appear in a later version of this paper.…”

Section: Discussionmentioning

confidence: 97%

“…Hence, as with the main algorithm of [5] which we are generalizing, there is a non-trivial amount of preprocessing to be done. This algorithm also generalizes the main algorithm of [7], wherein the authors break up the 4 × 4 perfect code into two groups of eight symbols, as well as the approach in [6] which studies the 3 × 3 perfect code.…”

Section: The General N × N Casementioning

confidence: 95%

“…The main algorithm of [5] reduces the decoding complexity of the Golden code from O(|S| 3 ), corresponding to the complexity of ML-decoding, to O(|S| 2 ), while maintaining nearly-ML performance. The algorithm is specific to the Golden code, but has been generalized to the 3×3 and 4×4 perfect codes in, respectively, [6] and [7]. The main contribution of this article is a recursive algorithm for decoding arbitrary n × n algebraic ST codes generalizing those of [5][6][7], which reduces the worst-case decoding complexity of…”

Section: Introductionmentioning

confidence: 99%

“…The algorithm is specific to the Golden code, but has been generalized to the 3×3 and 4×4 perfect codes in, respectively, [6] and [7]. The main contribution of this article is a recursive algorithm for decoding arbitrary n × n algebraic ST codes generalizing those of [5][6][7], which reduces the worst-case decoding complexity of…”

Section: Introductionmentioning

confidence: 99%

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Reduced Complexity Decoding of n x n Algebraic Space-Time Codes

Barreal,

Hollanti,

Karpuk

2015

Preprint

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Algebraic space-time coding allows for reliable data exchange across fading multiple-input multiple-output channels. A powerful technique for decoding space-time codes is Maximum-Likelihood (ML) decoding, but well-performing and widely-used codes such as the Golden code often suffer from high ML-decoding complexity. In this article, a recursive algorithm for decoding general algebraic space-time codes of arbitrary dimension is proposed, which reduces the worst-case decoding complexity from O(|S| n 2 ) to O(|S| n ).

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Section: Discussionmentioning

confidence: 97%

Section: The General N × N Casementioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reduced Complexity Decoding of n x n Algebraic Space-Time Codes

Barreal,

Hollanti,

Karpuk

2015

Preprint

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“…Given a finite signalling alphabet S ⊂ Z, the ML decoding complexity of a rank-k space-time code X is defined as the minimum number of values that have to be computed for finding the solution to (2). The upper bound is the worst-case decoding complexity that we denote by D(S), which for its part is upper bounded by the exhaustive search complexity, D(S) ≤ |S| k .…”

Section: Maximum-likelihood Decodingmentioning

confidence: 99%

On Fast-Decodable Algebraic Space--Time Codes

Barreal¹,

Hollanti²

2017

Preprint

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In the near future, the 5 th generation (5G) wireless systems will be established. They will consist of an integration of different techniques, including distributed antenna systems and massive multiple-input multiple-output systems, and the overall performance will highly depend on the channel coding techniques employed. Due to the nature of future wireless networks, spacetime codes are no longer merely an object of choice, but will often appear naturally in the communications setting. However, as the involved communication devices often exhibit a modest computational power, the complexity of the codes to be utilised should be reasonably low for possible practical implementation.Fast-decodable codes enjoy reduced complexity of maximum-likelihood (ML) decoding due to a smart inner structure allowing for parallelisation in the ML search. The complexity reductions considered in this chapter are entirely owing to the algebraic structure of the considered codes, and could be further improved by employing non-ML decoding methods, however yielding suboptimal performance.The aim of this chapter is twofold. First, we provide a tutorial introduction to space-time coding and study powerful algebraic tools for their design and construction. Secondly, we revisit algebraic techniques used for reducing the worst-case decoding complexity of both single-user and multiuser space-time codes, alongside with general code families and illustrative examples.

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On Fast-Decodable Algebraic Space–Time Codes

Barreal

Hollanti

2020

Number Theory Meets Wireless Communications

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Low Complexity Decoding of the 4×4 Perfect Space-time Block Code

Cited by 7 publications

References 11 publications

Reduced Complexity Decoding of n x n Algebraic Space-Time Codes

Reduced Complexity Decoding of n x n Algebraic Space-Time Codes

On Fast-Decodable Algebraic Space--Time Codes

On Fast-Decodable Algebraic Space–Time Codes

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