Adaptive PRB Bundling for Channel Estimation in Open Loop Beamforming
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Solution Overview
Problem
Current wireless communication systems face inefficiencies in channel estimation performance due to the reduction in the number of precoders used for small data allocation sizes when physical resource blocks are bundled, which can offset the gains achieved by PRB bundling.
Innovation Solution
The bundling of physical resource blocks is made dependent on the data allocation size, with bundling enabled or disabled based on the available number of precoders, and the actual bundling size determined accordingly, allowing for the use of a common precoding matrix across bundled resource blocks to improve channel estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical resource blocks are bundled with a common precoding matrix, then channel estimation performance is improved through joint estimation across resource blocks, but the number of precoders available for small data allocation sizes is reduced, offsetting the performance gains
Solution Approach 1:
The patent applies dynamics by making the bundling configuration adaptive rather than static. The network can dynamically adjust the bundling size and precoder assignment based on current channel conditions, data allocation size, and mobility state. This allows the system to optimize channel estimation performance when beneficial while maintaining sufficient precoder diversity when needed, resolving the contradiction between these two parameters.
Solution Approach 2:
The patent changes the parameter of bundling size from a fixed value to a variable that can be adjusted based on data allocation size. By modifying this parameter dynamically, the system can enable larger bundling sizes for large allocations (improving channel estimation) while using smaller or no bundling for small allocations (preserving precoder quantity), thus resolving the technical contradiction.
2Measurement precision
If bundling size is increased to improve channel estimation through joint processing, then estimation accuracy improves, but the flexibility to maintain sufficient precoder diversity for different allocation sizes is reduced
Solution Approach 1:
The system dynamically adjusts bundling configuration based on real-time conditions including data allocation size, channel coherence, and mobility state. This dynamic adaptation allows the system to achieve high channel estimation accuracy when conditions permit while maintaining flexibility in precoder assignment when conditions require it, resolving the contradiction between accuracy and adaptability.
Solution Approach 2:
The patent applies local quality by allowing different bundling configurations for different parts of the resource allocation. Instead of applying a uniform bundling size across all allocations, the system can apply different bundling sizes or no bundling at all depending on the local conditions of each data allocation, thus maintaining both accuracy where needed and flexibility where required.
3Device complexity
If PRB bundling is applied uniformly across all data allocation sizes, then channel estimation is simplified through joint processing, but performance is degraded for small allocations due to insufficient precoder diversity
Solution Approach 1:
The patent applies local quality by making bundling configuration data allocation-specific. For large data allocations, the system applies PRB bundling with common precoding matrices to simplify channel estimation. For small data allocations, the system uses smaller or no bundling to maintain precoder diversity and ensure reliable channel estimation. This localized approach resolves the contradiction between simplification and performance.
Solution Approach 2:
The system changes the bundling parameter based on data allocation size. By making the bundling size a variable parameter rather than a fixed value, the system can reduce or eliminate bundling for small allocations (maintaining reliability) while enabling bundling for large allocations (achieving complexity reduction), thus resolving the technical contradiction.
Data Source
AI summary
Provided is a method for wireless communication which includes determining a data allocation size available for data to be transmitted, determining a bundling size based at least in part on the data allocation size, and precoding at least one reference signal in bundled contiguous resource blocks of the determined bundling size. The at least one reference signal in resource blocks in each bundle are precoded with a common precoding matrix.