Scrambled Payload LLR Combining for 5G Polar Decoding
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Solution Overview
Problem
Current 5G NR technology faces challenges in decoding performance due to poor minimum distance of Polar codes, especially for lower code sizes, which affects the transmission and reception of data, and existing techniques for combining scrambled payloads over multiple transmissions are not effective in 5G NR systems.
Innovation Solution
The proposed method involves generating a second payload with selectively set payload mask bits to remove the impact of scrambling both before and after encoding, allowing for the combination of log likelihood ratios (LLRs) from multiple transmissions to improve decoding performance by descrambling the received LLRs and combining them for better error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If Polar codes are used for error-correction in 5G NR systems, then spectral efficiency is improved, but decoding performance deteriorates due to poor minimum distance for lower code sizes
Solution Approach 1:
The patent segments the decoding process into multiple iterations, where each iteration refines the decoding of scrambled payloads. The decoder performs initial decoding, identifies unsuccessfully decoded payloads, retrieves corresponding soft bits, re-encodes them, and combines with previously decoded payloads. This segmented approach allows the system to maintain Polar code spectral efficiency while improving overall decoding performance through iterative refinement.
Solution Approach 2:
The patent applies preliminary action by pre-processing received signals to extract soft bits corresponding to scrambled payloads before the main decoding process. The system prepares reference signals, channel estimates, and initial decoding results in advance, which are then used to guide the iterative decoding process. This preliminary preparation enables more effective decoding of Polar codes with poor minimum distance.
2Reliability
If scrambled payloads are combined over multiple transmissions, then error correction is improved, but the complexity of combining decision metrics increases due to double scrambling
Solution Approach 1:
The patent segments the combining process by separating the handling of scrambled and unscrambled components. The system identifies which payloads were successfully decoded and which require further processing, then applies different combining strategies to each segment. Successfully decoded payloads are finalized, while unsuccessfully decoded payloads undergo iterative re-decoding with combined decision metrics from multiple transmissions, reducing overall complexity.
Solution Approach 2:
The patent introduces an intermediary process of retrieving and re-encoding soft bits of unsuccessfully decoded payloads. This intermediary step creates a bridge between the received scrambled signals and the decoding process, allowing the system to combine decision metrics effectively. The re-encoded versions serve as intermediaries that facilitate the combining operation without requiring direct manipulation of the complex doubly-scrambled signals.
3Reliability
If iterative decoding of unsuccessfully decoded payloads is performed, then decoding performance is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by performing iterative decoding only on unsuccessfully decoded payloads rather than all received payloads. The system identifies which specific payloads failed initial decoding and limits the iterative process to those cases. This selective approach improves decoding performance where needed while avoiding unnecessary processing time for successfully decoded payloads, optimizing the trade-off between reliability and processing time.
Solution Approach 2:
The patent implements skipping by rapidly processing successfully decoded payloads and moving them forward in the transmission pipeline, while concentrating processing resources on unsuccessfully decoded payloads. The system skips detailed iterative processing for payloads that are already correctly decoded, rushing them through to finalization, and only applies time-consuming iterative decoding to the subset of payloads that require it, thereby reducing overall processing time.
Data Source
AI summary
Certain aspects of the present disclosure generally relate to techniques for combining a plurality of decision metrics of a scrambled payload in a 5G wireless communications system. For example, in some cases, combining decision metrics of a scrambled payload may generally involve receiving a first payload at a receiver that was scrambled both before and after encoding, generating a second payload at the receiver with selectively set payload mask bits, and using the selectively-set payload mask bits in the second payload to descramble the first payload.