Space-Time Block Coding With Mutual Orthogonality for Fast ML Decoding
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Solution Overview
Problem
Existing Space-Time Block Codes (STBCs) face challenges in achieving low-complexity maximum-likelihood (ML) decoding while maintaining desired diversity order and coding rate, especially with multiple-input multiple-output (MIMO) systems, where the complexity of ML decoding is high due to large codebooks and high Signal-to-Noise Ratio (SNR) performance issues.
Innovation Solution
The method generates linear STBCs by decomposing the transmission matrix into linear dispersion matrices, ensuring orthogonality between columns of the equivalent channel matrix through a novel component-wise mutual orthogonality criterion, which reduces decoding complexity by introducing zero entries in the upper triangular matrix, allowing for reduced-complexity ML decodable codes with arbitrary antenna numbers and coding rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional STBC schemes are used to achieve full diversity and high coding rate, then the transmission reliability is improved, but the ML decoding complexity increases significantly
Solution Approach 1:
The patent applies segmentation by dividing the STBC design into two independent parts: (1) selecting weight matrices that satisfy orthogonality conditions for full diversity, and (2) choosing permutation matrices that enable low-complexity decoding. This segmentation allows the system to achieve both full diversity and reduced decoding complexity simultaneously by treating these as separate design dimensions rather than conflicting requirements.
Solution Approach 2:
The patent introduces a new dimension to the STBC design space by incorporating permutation matrices as a separate degree of freedom. Instead of only optimizing weight matrices, the invention adds the permutation dimension, which transforms the decoding complexity issue into a matrix reordering problem. This dimensional expansion allows independent optimization of diversity performance and decoding complexity.
2Device complexity
If orthogonal designs are used to achieve fast ML decoding, then the decoding complexity is reduced, but the coding rate is limited to one or lower for more than four transmit antennas
Solution Approach 1:
The patent changes the parameter space by introducing permutation matrices as an additional design variable. This allows the system to maintain orthogonality conditions for fast decoding while varying the permutation parameters to achieve different coding rates. The permutation matrices provide flexibility to adjust the coding rate without compromising the orthogonality-based low-complexity decoding property.
3Productivity
If quasi-orthogonal designs are used to improve symbol rates, then the coding rate increases, but the orthogonality is relaxed and diversity gain is reduced
Solution Approach 1:
The patent segments the code design into weight matrices (ensuring orthogonality for full diversity) and permutation matrices (enabling high coding rates). This segmentation allows the system to maintain strict orthogonality in the weight matrices for full diversity while using permutation matrices to achieve high symbol rates, avoiding the need to relax orthogonality as in quasi-orthogonal designs.
Data Source
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AI summary
There is provided a method of generating a space-time block code (STBC) for encoding a digital data sequence comprising a set of independent symbols to be transmitted through a transmission channel in a communication system, the space-time block code being represented by a set of linear dispersion matrices in a linear dispersion representation, each linear dispersion matrix comprising components having complex values, the method comprising, generating at least some of the linear dispersion matrices depending on component-wise conditions related to a set of selected pairs of the linear dispersion matrices, each pair comprising a first linear dispersion matrix and a second linear dispersion matrix, said component-wise conditions comprising a component-wise condition between the components of the first linear dispersion matrix and the components of the second linear dispersion matrix.