Wireless Feedback Compression via Codebook Selection
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Solution Overview
Problem
As transmission throughput increases in wireless communication systems, the amount of feedback values to be transmitted also increases, leading to higher bandwidth requirements and potential reliability issues, particularly in 5G NR systems with higher frequency bands and massive MIMO configurations, where the HARQ feedback payload size becomes significant and inefficient.
Innovation Solution
Implementing a compression method using a selected codebook to compress multiple feedback values for multiple code blocks into a single compressed feedback value, reducing the number of bits required for transmission and maintaining high reliability, while allowing for efficient decompression to retrieve original feedback values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If transmission throughput increases, then data transmission capacity improves, but feedback payload size increases proportionally
Solution Approach 1:
The patent merges multiple feedback values into a single compressed feedback value by grouping code blocks and applying compression algorithms. This combining approach reduces the total number of feedback bits while maintaining the ability to identify individual code block status, directly resolving the contradiction between throughput and payload size.
Solution Approach 2:
The patent changes the parameter representation from individual feedback bits for each code block to a compressed representation using algorithms like Huffman coding. This parameter transformation reduces the quantity of feedback data while preserving the necessary information for reliable communication.
2Loss of information
If feedback payload size increases, then feedback information completeness improves, but bandwidth requirements increase
Solution Approach 1:
Multiple feedback values are merged into a compressed feedback value that maintains information completeness. The compression algorithm preserves all necessary feedback information while reducing the number of bits transmitted, thus maintaining feedback completeness while reducing bandwidth requirements.
Solution Approach 2:
The patent uses codebooks that contain pre-defined compressed feedback representations. Instead of transmitting raw feedback values, the system transmits indices or references to pre-computed compressed representations, reducing bandwidth while maintaining information completeness.
3Measurement precision
If feedback payload size increases, then feedback resolution improves, but reliability decreases
Solution Approach 1:
The patent merges feedback values in a way that preserves resolution through the compression algorithm. By using lossless compression and maintaining the ability to distinguish between different code block states, the system achieves both high resolution and reliability in the compressed feedback.
Solution Approach 2:
The system implements feedback mechanisms to verify compression accuracy and ensure reliable feedback transmission. The compressed feedback includes information that allows the receiving end to verify the feedback integrity, maintaining reliability while reducing payload size.
Data Source
AI summary
Aspects described herein relate to receiving a configuration including one or more parameters related to compressing feedback values for multiple code blocks, performing, using a compression method and an associated codebook that are selected using the one or more parameters, a compression of multiple feedback values for a set of code blocks received from a network device into a compressed feedback value, and transmitting, to the network device and using the compressed feedback value, compressed feedback for the set of code blocks.