MIMO Channel Capacity Based MCS Selection
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Solution Overview
Problem
In wireless communication systems, existing methods like Exponential Effective SINR Mapping are challenging to apply for multiple-input multiple-output (MIMO) nonlinear detectors, making it difficult to accurately select a suitable modulation and coding scheme (MCS) for improving throughput.
Innovation Solution
A receiving device and method that includes a channel estimation unit, eigenvalue computation unit, channel compensation unit, channel capacity computation unit, and selection unit to determine a modulation and coding scheme based on channel estimates, eigenvalues, and correlation compensation values, enabling accurate MCS selection for both linear and nonlinear detectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If Exponential Effective SINR Mapping (EESM) is used to select MCS, then the MCS selection is simple and suitable for linear detectors, but it cannot be accurately applied to MIMO nonlinear detectors
Solution Approach 1:
The patent transforms the channel quality assessment from using SINR values directly (as in EESM) to using eigenvalues derived from the channel correlation matrix. This parameter transformation enables accurate channel capacity estimation for nonlinear detectors by capturing the spatial correlation characteristics of MIMO channels, thereby resolving the inaccuracy of EESM for nonlinear detection scenarios.
2Device complexity
If traditional MCS selection methods are used, then the implementation is straightforward, but the throughput improvement is limited due to inaccurate channel condition assessment
Solution Approach 1:
The patent performs preliminary computation of the channel correlation matrix and its eigenvalues before MCS selection. By pre-processing the channel estimates to extract eigenvalue characteristics that represent channel capacity, the system enables more accurate MCS determination that directly improves throughput, while the pre-computed eigenvalues facilitate straightforward implementation of the enhanced selection criterion.
3Device complexity
If channel capacity is determined without correlation compensation, then the computation is simpler, but the MCS determination accuracy deteriorates under correlated channel conditions
Solution Approach 1:
The patent addresses correlation effects by transforming the channel capacity computation to operate on eigenvalues of the channel correlation matrix rather than directly on channel estimates. This parameter transformation inherently accounts for spatial correlation in MIMO channels, improving channel capacity estimation accuracy without requiring complex compensation algorithms, thus maintaining computational simplicity while enhancing precision.
Data Source
AI summary
A receiving device comprises a channel estimation unit, for generating a plurality of channel estimates according to a plurality of reference signals; an eigenvalue computation unit, coupled to the channel estimation unit, for generating at least one eigenvalue corresponding to the plurality of channel estimates according to the plurality of channel estimates; a channel compensation unit, coupled to the eigenvalue computation unit, for generating a correlation compensation value for compensating the plurality of channels according to the at least one eigenvalue; a channel capacity computation unit, coupled to the eigenvalue computation unit and the channel compensation unit, for generating a channel capacity according to the at least one eigenvalue and the correlation compensation value; and a selection unit, coupled to the channel capacity computation unit, for determining a modulation and coding scheme (MCS) according to the channel capacity.