DCI Wakeup Signal Detection Using Identifier Functions
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Solution Overview
Problem
In wireless communication networks, particularly in LTE and NR systems, there is a need to balance the detection of wake-up signals (WUS) to reduce unnecessary power consumption by user equipment (UE) while minimizing missed detections and false activations of the PDCCH decoder.
Innovation Solution
The solution involves transmitting wake-up signals (WUS) using downlink control information (DCI) with identifiers like C-RNTI or WUG-RNTI, where the payload and CRC portions are based on specific functions of these identifiers, such as truncation, repetition, or scrambling, to enhance detection accuracy and reduce false alarms, thereby optimizing the UE's energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wake-up signals are transmitted using DCI with identifier-based payload and CRC scrambling, then detection accuracy is improved and false alarms are reduced, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent applies preliminary action by pre-defining the relationship between identifiers and their functions (truncation, repetition, scrambling) before transmission. The network node prepares the DCI payload and CRC portions using predetermined functions of the identifier, allowing the UE to efficiently verify the signal without complex real-time analysis. This pre-established structure improves detection accuracy while controlling processing complexity.
2Reliability
If the UE continuously monitors PDCCH for wake-up signals, then detection reliability is improved, but power consumption increases
Solution Approach 1:
The patent implements periodic action by enabling the UE to enter sleep mode and wake up at predetermined intervals to monitor for DCI-based wake-up signals. Instead of continuous monitoring, the UE periodically checks for signals containing its identifier or group identifier in the payload or CRC portions. This periodic monitoring approach maintains detection reliability while significantly reducing power consumption compared to continuous monitoring.
3Speed
If simple identifier matching is used for wake-up signal detection, then processing speed is improved, but detection precision deteriorates due to false alarms
Solution Approach 1:
The patent applies segmentation by dividing the identifier usage into distinct functional segments: one portion (or function) is used in the DCI payload portion while another portion (or function) is used in the CRC portion. This segmentation allows the UE to perform efficient processing by checking different parts of the identifier in different contexts, improving both processing speed and detection precision by reducing false alarms through multi-point verification.
Solution Approach 2:
The patent implements local quality by applying different processing functions to different parts of the identifier. Rather than uniformly processing the entire identifier, the system applies specific functions (truncation, repetition, scrambling) to specific portions or aspects of the identifier in different contexts (payload vs. CRC). This localized differentiation improves detection precision while maintaining processing efficiency.
Data Source
AI summary
Exemplary embodiments include methods for a user equipment (UE) to receive a wake-up signal (WUS) via downlink control information (DCI) transmitted by a network node in a radio access network (RAN). Such methods include receiving a physical downlink control channel (PDCCH) from the network node, and processing the received PDCCH to determine if it includes a DCI carrying a WUS targeted to the UE. The processing can include determining if a payload portion of the DCI is based on a first function of an identifier associated with the UE (e.g., C-RNTI) or with a group of UEs (e.g., WUG-RNTI). The processing can also include determining if a cyclic redundancy check (CRC) portion of the DCI is based on a second function of the identifier. Other embodiments include complementary methods performed by a network node, and UEs or network nodes configured to perform the exemplary methods.