Soft Information Compression for LTE Decoding
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Solution Overview
Problem
In wireless communication systems using the 3GPP LTE protocol, storing soft information values for failed decoding attempts results in significant storage and bandwidth requirements, which can impose a substantial load on memory resources, especially in high data rate systems.
Innovation Solution
The method involves compressing soft information values before storage, reducing memory size and bandwidth requirements, while maintaining system throughput performance by using either internal or external memory, and decompressing them for combined decoding attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If soft information values are stored without compression, then decoding accuracy is maintained, but memory size and bandwidth requirements increase significantly
Solution Approach 1:
The patent applies parameter changes by compressing the soft information values from their original format (e.g., 8-bit LLR values) to a compressed representation that requires less storage space. This compression reduces the quantity of data stored while maintaining the essential information needed for accurate decoding, thus resolving the contradiction between memory size and decoding accuracy.
Solution Approach 2:
The patent creates a compressed copy of the soft information values that can be stored efficiently in memory. Instead of storing the full-precision soft information, a compressed representation is created and stored, which can later be decompressed and combined with subsequent transmissions to achieve accurate decoding without requiring proportional memory resources.
2Quantity of substance
If soft information values are compressed before storage, then memory size and bandwidth requirements are reduced, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by performing compression of soft information values immediately when they are generated, before storage or further processing. This upfront compression step reduces the data volume that needs to be managed throughout the subsequent HARQ process, making the overall system more efficient despite the added compression step.
3Quantity of substance
If compressed soft information values are stored, then memory costs are reduced, but decompression and combining operations require additional processing time
Solution Approach 1:
The patent uses parameter changes through compression and decompression operations that transform the soft information values between compressed and uncompressed formats. The compression ratio and decompression algorithm are designed to minimize processing overhead while achieving significant memory savings, thus balancing the trade-off between storage capacity and processing time.
Data Source
AI summary
Method, receiver and computer program product for decoding a coded data block received at the receiver are disclosed. A first plurality of coded data bits representing the coded data block are received. First soft information values are determined corresponding to respective ones of the received first plurality of coded data bits, wherein each of the soft information values indicates a likelihood of a corresponding coded data bit having a particular value. An attempt is made to decode the coded data block using the first soft information values. The first soft information values are compressed. The compressed first soft information values are stored in a data store. A second plurality of coded data bits representing the coded data block is received and second soft information values corresponding to respective ones of the received second plurality of coded data bits are determined. The compressed first soft information values are retrieved from the data store and decompressed. The decompressed first soft information values are combined with the second soft information values, and an attempt is made to decode the coded data block using the combined soft information values.