Mixed-Mode MIMO Detector Sub-Channel Allocation
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Solution Overview
Problem
Current wireless access points (WAPs) face challenges in efficiently detecting Multiple-Input Multiple-Output (MIMO) communications due to high complexity and resource requirements, especially in environments with varying channel conditions.
Innovation Solution
A mixed-mode MIMO detector is implemented in wireless devices, allocating a mix of linear and non-linear MIMO detectors across OFDM sub-channels based on channel correlation, optimizing resource usage and reducing complexity by assigning less complex detectors to less correlated sub-channels and more complex detectors to highly correlated ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-linear MIMO detectors are used exclusively for MIMO detection, then signal resolution capability is improved, but processing complexity and resource requirements increase significantly
Solution Approach 1:
The patent applies local quality by differentiating detection approaches across different sub-channels based on their specific channel conditions. Linear detectors are assigned to sub-channels with low correlation where they provide sufficient performance with lower complexity, while non-linear detectors are assigned to sub-channels with high correlation where their superior signal resolution capability is needed. This localized adaptation resolves the contradiction by optimizing the match between detector capability and channel requirements.
Solution Approach 2:
The patent changes the parameter of detector type selection based on channel correlation characteristics. By evaluating channel conditions and dynamically assigning appropriate detector types (linear vs. non-linear) to different sub-channels, the system adapts its processing complexity to match the actual signal conditions, thereby achieving good signal resolution only where necessary while reducing overall processing burden.
2Measurement precision
If non-linear MIMO detectors are used exclusively for MIMO detection, then detection accuracy is improved, but processing time and resource consumption increase
Solution Approach 1:
The patent implements local quality by applying different detection strategies to different sub-channels based on their correlation properties. Sub-channels with low correlation use computationally efficient linear detectors that process quickly, while sub-channels with high correlation use more accurate but computationally intensive non-linear detectors. This resolves the time-accuracy contradiction by ensuring high accuracy is achieved only where channel conditions warrant it.
Solution Approach 2:
The patent applies partial action by using non-linear detectors only for the portion of sub-channels that require their enhanced capability (those with high correlation), rather than applying them universally. This selective application reduces overall processing time while maintaining detection accuracy where it matters most, avoiding the excessive processing time that would result from universal non-linear detector deployment.
3Device complexity
If linear MIMO detectors are used for all sub-channels, then processing complexity is reduced, but signal resolution capability deteriorates in highly correlated channels
Solution Approach 1:
The patent resolves this contradiction by making detector selection local to each sub-channel's characteristics. Linear detectors are deployed on sub-channels with low correlation where they provide adequate performance with minimal complexity, while non-linear detectors are deployed on sub-channels with high correlation where signal resolution capability is compromised by using linear detectors alone. This localized differentiation ensures neither complexity nor resolution capability is suboptimal.
Solution Approach 2:
The patent changes the detector type parameter based on channel correlation measurements. By evaluating the correlation parameter of each sub-channel and selecting the appropriate detector type accordingly, the system ensures that signal resolution capability is maintained in high-correlation channels while keeping processing complexity low in low-correlation channels, thus resolving the contradiction between these two parameters.
4Device complexity
If uniform detector allocation is used across all sub-channels, then device complexity is reduced, but adaptability to varying channel conditions deteriorates
Solution Approach 1:
The patent applies local quality by allocating detectors based on local channel characteristics rather than using a uniform allocation strategy. Each sub-channel is evaluated for its correlation properties, and detector type is selected locally to match those conditions. This provides adaptability to varying channel conditions while maintaining relatively simple device complexity through automated selection logic, resolving the contradiction between uniformity and adaptability.
Solution Approach 2:
The patent introduces dynamics into the detector allocation process by making detector selection dependent on channel conditions rather than being static and uniform. The system dynamically evaluates channel correlation and adjusts detector allocation accordingly, enabling adaptability to varying channel conditions while keeping the overall device complexity manageable through systematic selection criteria.
Data Source
AI summary
A wireless device with multiple antennae and configured to support orthogonal frequency-division multiplexed (OFDM), multiple-input multiple-output (MIMO) communications of a wireless local area network (LAN) among multiple wireless devices over a shared wireless communication medium on a shared communication channel. The wireless access device comprises: a mixed-mode MIMO detector configured to allocate a mix of linear and non-linear MIMO detectors among received OFDM sub-channels of the shared communication channel, thereby reducing a level of complexity associated with reception of MIMO streams exclusively via non-linear MIMO detectors.


