MIRS Feedback Compression Using Decoding-Probability Codebooks
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Solution Overview
Problem
Current wireless communication systems face inefficiencies in transmitting feedback information due to the high number of bits required for retransmissions in protocols like HARQ and MIRS, which can impact system performance and bandwidth usage.
Innovation Solution
Implementing lossy compression methods that select a different compression codebook per feedback group based on the probability of successful decoding, reducing the number of feedback bits by adjusting compression according to dynamic transmission characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feedback information is transmitted using traditional uncompressed methods in HARQ and MIRS protocols, then reliability of data transmission is maintained, but bandwidth consumption increases and system performance deteriorates
Solution Approach 1:
The patent divides feedback information into multiple groups (first feedback group, second feedback group, etc.) corresponding to different symbols or time slots. Each group is compressed independently using separate codebooks, allowing selective application of compression strategies based on local characteristics while maintaining overall reliability.
Solution Approach 2:
The patent dynamically selects compression codebooks based on probability of successful decoding for each code block. By changing the compression parameter (codebook selection) according to decoding probability, the system adapts the compression level to maintain reliability where needed while reducing bandwidth where possible.
2Device complexity
If a single compression codebook is used for all feedback groups, then device complexity is reduced, but adaptability to changing channel conditions deteriorates
Solution Approach 1:
Multiple compression codebooks are maintained, with each codebook associated with specific feedback groups or symbols. This segmentation allows the system to select appropriate codebooks based on channel conditions and decoding probabilities, improving adaptability while keeping individual codebook management relatively simple.
Solution Approach 2:
The system dynamically selects which compression codebook to apply to each feedback group based on the probability of successful decoding and channel conditions. This dynamic adaptation allows the system to respond to changing transmission conditions without requiring complex real-time codebook generation.
Data Source
AI summary
Various embodiments may provide systems and methods for supporting lossy compression of feedback information, such as acknowledgment (ACK) information, negative acknowledgement (NACK) information, etc. Various embodiments may support lossy compression for feedback messages in retransmission systems, such as Hybrid Automatic Repeat Request (HARD) protocols, the Multiple Incremental Redundancy Scheme (MIRS), etc. Various embodiments may support compression of feedback bits using a different compression codebook per symbol or per group of symbols. Various embodiments may support selection of a compression codebook per symbol, or per group of symbols, based at least in part on a probability of successful decoding of each code block in the symbol or group of symbols.