Correlation-Based Channel Feedback for Spatial Streams
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Solution Overview
Problem
As the number of spatial streams increases in wireless communication, the duration and size of sounding signals and channel feedback information grow linearly, leading to increased complexity in generating channel feedback, which can overwhelm receiver capabilities, especially when the number of transmit antennas exceeds the receiver's capacity for providing feedback.
Innovation Solution
The method involves partitioning spatial streams into orthogonal sets, determining separate channel estimates and correlations for each set, and averaging these correlations to reduce the complexity of eigenvalue decomposition, allowing for efficient channel feedback generation even with a large number of spatial streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of spatial streams is increased to achieve beamforming gains, then beamforming performance is improved, but the duration and size of sounding signals and channel feedback information increase linearly, leading to increased processing complexity
Solution Approach 1:
The patent divides the spatial streams into multiple groups and performs channel feedback generation separately for each group. This segmentation allows the receiver to process fewer streams simultaneously, reducing the computational complexity of eigenvalue decomposition while still supporting a large total number of spatial streams through grouped processing.
Solution Approach 2:
The patent performs preliminary channel estimation and correlation calculation for each group of spatial streams before combining the results. By preparing the channel feedback information in advance for each group separately, the system reduces the peak processing complexity that would occur if all streams were processed simultaneously.
2Adaptability or versatility
If the number of spatial streams is increased, then beamforming capability is enhanced, but the size of channel feedback information increases linearly, overwhelming receiver capabilities
Solution Approach 1:
The patent segments the channel feedback information into multiple groups corresponding to different sets of spatial streams. Each group contains feedback for a manageable subset of streams, allowing the receiver to process and store feedback information in smaller, organized units rather than as one large monolithic data structure.
Solution Approach 2:
The patent generates channel feedback for all spatial streams by processing groups partially and separately, then combining the results. This approach produces complete feedback information for all streams while avoiding the need to generate and transmit all feedback data simultaneously, thus managing the quantity of feedback information in a controlled manner.
3Productivity
If the number of transmit antennas exceeds the receiver's capacity for providing feedback, then more spatial streams can be transmitted, but the complexity of generating channel feedback increases significantly
Solution Approach 1:
The patent divides the set of all spatial streams into multiple smaller groups and processes each group independently for channel feedback generation. This segmentation enables the receiver to handle feedback for more total spatial streams than its raw processing capacity would allow, by distributing the computational load across multiple smaller, manageable tasks.
Solution Approach 2:
The patent introduces a grouping dimension to the feedback generation process, organizing spatial streams into multiple groups that can be processed in parallel or sequentially. This additional organizational dimension allows the system to scale to more spatial streams by adding groups rather than increasing the complexity of processing each individual stream.
Data Source
AI summary
This disclosure provides methods, devices and systems for providing channel feedback for multiple spatial streams. In some implementations, the techniques involve generating distinct channel estimates for different respective sets of orthogonal spatial streams. In some implementations, the orthogonality of the different sets of orthogonal spatial streams enables the beamformee to distinguish the spatial streams to provide the separate channel estimates. The beamformee may then determine separate correlations for the different respective sets of spatial streams. In some implementations, the beamformee combines the correlations to determine an average correlation for each of a number of sets of frequency tones. The beamformee may then perform an eigenvalue decomposition on a tone-by-tone basis based on the respective average correlation and the channel estimate obtained for the tone. Because the eigenvalue decomposition may be performed on each of the two sets of spatial streams separately, the complexity involved with performing each eigenvalue decomposition is greatly reduced.