Two-Step Precoder Selection Reducing Computational Load
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Solution Overview
Problem
As the number of antenna elements in wireless communication networks increases, existing approaches to precoding control do not scale well, leading to significant computational burdens and increased power consumption for wireless devices, which affects battery life and CSI reporting efficiency, especially in resource-scarce channels like PUCCH.
Innovation Solution
A method involving a two-step precoder selection process, where a reduced set of precoders is first identified through simpler evaluations, followed by more complex evaluations within this set to determine the preferred precoder for use in precoding transmissions, thereby reducing the overall computational burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of antenna ports is increased to support more transmission layers and improve spectral efficiency, then the system capacity and throughput are improved, but the number of feedback bits required in the CSI report increases significantly, leading to increased overhead especially on PUCCH
Solution Approach 1:
The patent extracts only the most relevant precoders from the full codebook by identifying a limited set of candidate precoders based on channel conditions. Instead of reporting all possible precoders, the system extracts and reports only those that are most likely to be optimal, significantly reducing feedback overhead while maintaining throughput performance.
Solution Approach 2:
The patent applies partial action by evaluating and reporting only a subset of precoders rather than the complete codebook. The UE performs partial codebook evaluation focusing on promising candidates identified through channel quality indicators, thereby achieving sufficient precoder selection accuracy with reduced feedback bits.
2Adaptability or versatility
If the size of the precoder codebook is expanded to support more antenna ports and transmission layers, then the adaptability of the system is improved, but the computational burden and power consumption for evaluating and reporting preferred precoders increase significantly
Solution Approach 1:
The patent segments the large precoder codebook into manageable subsets or categories. By dividing the codebook evaluation into stages (initial candidate identification followed by refined selection), the system reduces the computational complexity at each step, thereby lowering power consumption while maintaining the ability to handle large codebooks for many antenna ports.
Solution Approach 2:
The patent applies preliminary action by performing initial channel quality assessment and candidate precoder identification before detailed precoder evaluation. This preliminary filtering step eliminates obviously suboptimal precoders early in the process, reducing the number of computationally intensive operations required and thereby reducing power consumption.
3Measurement precision
If the number of bits in the CSI report is increased to indicate the desired precoder from larger codebooks, then the precision of precoder indication is improved, but the resource overhead on PUCCH increases significantly
Solution Approach 1:
The patent inverts the traditional approach by having the network configure the codebook and precoder selection criteria, then having the UE report only the index or identifier of the selected precoder from this pre-configured set. This inversion of roles and pre-agreement on codebook structure enables accurate precoder indication with fewer feedback bits.
Data Source
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AI summary
Culling a set of precoders down to a smaller set using a comparatively simple first-pass evaluation allows a wireless device or other entity to reduce an overall computational burden associated with identifying a currently preferred precoder. An example approach involves selecting a reduced set of precoders from a full set of precoders, based on performing preliminary evaluations of precoders in the full set, and selecting a preferred precoder or precoders from the reduced set, based on performing further evaluations of precoders in the second set. On a per precoder basis, the further evaluations are more complex than the preliminary evaluations. One may view the approach as using less complex first-pass evaluations to reduce the precoder search space, and then using more complex second-pass evaluations to identify a currently preferred precoder or precoders within the reduced search space.