Blind Decoding Multiple DCI Sizes in Wireless Control Channels
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Solution Overview
Problem
Current wireless communication systems face inefficiencies in decoding downlink control information (DCI) due to the need for separate decoding processes for multiple DCI sizes, which increases processing latency and complexity.
Innovation Solution
The method involves determining a first hypothesis among multiple hypotheses for decoding DCI based on different sizes, allowing for joint decoding of multiple DCI sizes with a single decoding process and subsequent cyclic redundancy checks (CRC) to determine the extracted information bits, thereby reducing processing and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate decoding processes are performed for multiple DCI sizes, then decoding accuracy is maintained, but processing latency and complexity increase
Solution Approach 1:
The patent merges multiple separate decoding processes into a single unified blind decoding process. The UE determines multiple hypotheses regarding DCI parameters (aggregation level, CCE size, DCI size) and performs joint decoding based on these hypotheses, then extracts information bits for each hypothesis and performs CRC checks to determine successful decoding. This combining of multiple decoding operations into one process reduces processing latency while maintaining decoding accuracy through the hypothesis-based approach.
Solution Approach 2:
The patent creates a universal decoding mechanism that handles multiple DCI sizes simultaneously. By establishing hypotheses that cover different DCI sizes, aggregation levels, and CCE configurations, the system achieves multi-functionality where a single decoding process can successfully decode DCI messages of various sizes and formats, eliminating the need for separate dedicated decoding processes for each DCI size.
2Reliability
If separate decoding processes are performed for multiple DCI sizes, then decoding reliability is maintained, but device complexity increases
Solution Approach 1:
The patent combines multiple decoding operations into a single integrated process. Instead of implementing separate decoding chains for different DCI sizes, the UE determines multiple hypotheses and performs one unified blind decoding operation that evaluates all hypotheses simultaneously through information bit extraction and CRC verification, thereby reducing device complexity while preserving decoding reliability.
Solution Approach 2:
The patent manages complexity by dynamically adjusting decoding parameters based on hypothesized DCI characteristics. The UE determines hypotheses about DCI size, aggregation level, and CCE configuration, then adapts the decoding process to these parameters. This parameter-based approach allows the system to handle multiple DCI formats flexibly without requiring hard-coded separate processing paths for each format, thus reducing overall device complexity.
Data Source
AI summary
Aspects described herein relate to decoding downlink control information (DCI) based on multiple DCI sizes. A first hypothesis of multiple hypotheses for decoding a communication received in a control channel search space, wherein the multiple hypotheses are based on different corresponding DCI sizes can be determined. The communication received in the control channel search space can be decoded based on the first hypothesis. For each of the multiple hypotheses and based on the different corresponding DCI sizes, information bits can be extracted from the communication as decoded. For each extracting of the information bits, cyclic redundancy check (CRC) can be performed based on one of the different corresponding DCI sizes to determine whether extracting of the information bits yields DCI.