Polar-Code Blind Detection with UE-Specific Candidate Shortlisting
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Solution Overview
Problem
Current blind detection methods for LTE user equipment (UE) in finding its physical downlink control channel (PDCCH) allocation suffer from high Missing Detection Probability (Pmiss) and False Alarm Probability (PFA), especially in scenarios like eMBB, URLLC, and mMTC, where reliability and low latency are critical, due to excessive use of CRC bits in decoding multiple channel candidates.
Innovation Solution
The method involves generating a UE-specific frozen sequence based on a UE identifier (UEID) for polar code encoding, reducing the reliance on CRC bits by using a two-stage decoding process: the first stage uses a UE-specific frozen sequence to shortlist candidates, and the second stage performs error-detection code-assisted decoding on these candidates, with path metrics comparison to filter out incorrect candidates, thereby minimizing the use of CRC bits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional blind detection methods are used to scan all possible channel candidates, then the UE can detect its PDCCH allocation, but the False Alarm Probability increases due to excessive CRC bit usage in decoding multiple candidates
Solution Approach 1:
The patent segments the blind detection process into two distinct stages: a first decoding stage using UE-specific frozen sequences to generate a shortlist of candidates, and a second decoding stage using CRC bits only on the shortlisted candidates. This segmentation reduces the number of times CRC bits are used, thereby lowering False Alarm Probability while maintaining detection reliability.
Solution Approach 2:
The patent performs preliminary filtering of channel candidates in the first decoding stage before applying CRC-based error detection. By using UE-specific frozen sequences to pre-screen candidates and generate a shortlist, the system prepares the data structure in advance to minimize subsequent CRC bit usage, thus reducing false alarms while maintaining reliable detection.
2Measurement precision
If CRC bits are used for error detection in all channel candidates, then detection accuracy improves, but the complexity of the decoding process increases due to the large number of candidates
Solution Approach 1:
The patent divides the decoding process into two stages: a first stage that filters candidates using UE-specific frozen sequences without CRC overhead, and a second stage that applies CRC-based error detection only to the shortlisted candidates. This segmentation maintains detection accuracy through CRC verification while reducing decoding complexity by limiting CRC operations to a smaller subset of candidates.
Solution Approach 2:
The patent performs preliminary filtering of channel candidates using UE-specific frozen sequences before applying CRC-based error detection. This preliminary action reduces the number of candidates requiring complex CRC verification, thereby maintaining detection accuracy while significantly reducing the overall decoding process complexity.
3Reliability
If the number of channel candidates is increased to reduce Missing Detection Probability, then detection coverage improves, but the False Alarm Probability increases due to more decoding operations
Solution Approach 1:
The patent segments the detection process into two stages: a first stage that efficiently screens all channel candidates using UE-specific frozen sequences to ensure comprehensive coverage, and a second stage that applies CRC verification only to shortlisted candidates. This segmentation allows the system to evaluate a large number of candidates for completeness while limiting false alarm-generating CRC operations to a smaller subset.
Solution Approach 2:
The patent performs preliminary filtering of all channel candidates using UE-specific frozen sequences before applying CRC-based error detection. This preliminary action enables the system to maintain low Missing Detection Probability by evaluating all candidates while reducing False Alarm Probability by limiting subsequent CRC operations to only the most promising shortlisted candidates.
Data Source
AI summary
Methods and systems for blind detection. At the encoder, a code word is encoded using a polar coder, where the input vector includes a user equipment (UE)-specific frozen sequence in the frozen bit positions. At the decoder, a set of short listed channel candidates is generated based on decoding using the UE-specific frozen sequence.