PDCCH Candidate Pruning Using Mutual Information Thresholds
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Solution Overview
Problem
The complexity and power consumption of blind decoding in wireless communication systems, particularly in decoding physical downlink control channels (PDCCH), are increased due to the need to monitor a large number of PDCCH candidates and search spaces, which impacts end-to-end receive time.
Innovation Solution
Implementing mutual information (MI)-based pruning of PDCCH candidates using non-transparent precoding parameters, where UEs demodulate and calculate MI for each candidate, pruning those below a threshold to reduce the number of candidates requiring decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the UE monitors a large number of PDCCH candidates and search spaces to ensure reliable control information reception, then the reliability of control information reception is improved, but the device complexity and power consumption increase significantly
Solution Approach 1:
The patent applies preliminary action by performing mutual information calculation on PDCCH candidates before full blind decoding. The UE calculates MI metrics for each candidate based on DMRS scrambling seeds, prunes candidates below a threshold, and only performs full decoding on remaining candidates. This preliminary filtering reduces the number of full decodings required while maintaining reliable reception of valid PDCCH candidates.
Solution Approach 2:
The patent implements self-service through UE-specific non-transparent precoding parameters that enable the UE to self-identify its intended PDCCH candidates. By using UE-specific DMRS scrambling seeds and non-transparent precoding, the UE can independently calculate mutual information metrics and prune candidates without network assistance, reducing overall system complexity while maintaining reliability.
2Reliability
If the UE performs blind decoding on all PDCCH candidates to ensure no control information is missed, then the completeness of control information detection is improved, but the power consumption and processing time increase
Solution Approach 1:
The patent performs preliminary mutual information calculation and candidate pruning before full blind decoding. By calculating MI metrics using UE-specific DMRS scrambling seeds and comparing against a threshold, the UE identifies and prunes unlikely candidates, performing full decoding only on remaining candidates. This reduces power consumption while maintaining detection completeness for valid candidates.
Solution Approach 2:
The patent changes the parameter of candidate evaluation by introducing mutual information metrics based on DMRS scrambling seeds. Instead of uniformly decoding all candidates, the system uses MI parameters to differentiate between likely and unlikely candidates, enabling selective decoding that reduces power consumption while maintaining detection completeness for valid PDCCH candidates.
3Reliability
If the UE decodes all PDCCH candidates to ensure accurate control information reception, then the accuracy of control information decoding is improved, but the end-to-end receive time increases
Solution Approach 1:
The patent performs preliminary mutual information calculation and candidate pruning before full decoding. By quickly evaluating MI metrics for each candidate and pruning those below a threshold, the UE reduces the number of full decoding operations required. This maintains decoding accuracy for valid candidates while reducing end-to-end receive time by eliminating unnecessary decoding operations.
Solution Approach 2:
The patent applies skipping by rushing through the evaluation of unlikely PDCCH candidates using fast mutual information calculation based on DMRS scrambling seeds. Candidates below the MI threshold are skipped entirely, avoiding time-consuming full decoding operations. This maintains accuracy for valid candidates while significantly reducing overall processing time.
Data Source
AI summary
Aspects relate to mechanisms for mutual information (MI)-based physical downlink control channel (PDCCH) candidate pruning. A UE may receive a plurality of PDCCH candidates in a search space. Each of the PDCCH candidates includes a demodulation reference signal (DMRS) generated with the same scrambling seed and control information generated with one or more respective UE-specific non-transparent precoding parameters. The UE can prune the PDCCH candidates to identify at least one PDCCH candidate for decoding by generating the log-likelihood ratio (LLR) magnitudes of demodulated PDCCH candidates and calculating the mutual information based on the LLR magnitudes.


