HARQ-ACK Payload Reduction for Priority-Based UCI Multiplexing
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently multiplexing hybrid automatic repeat request-acknowledgement (HARQ-ACK) payloads with different priorities, particularly due to large payloads of low priority HARQ-ACK bits, which can lead to poor resource utilization and degradation of high priority channel performance.
Innovation Solution
Implementing methods for HARQ-ACK payload reduction through code block group (CBG) level compression or bundling, spatial bundling, and grouping HARQ-ACK bits based on group size, with configurations determined by higher layer signaling, to reduce the payload of low priority HARQ-ACK bits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If HARQ-ACK with different priorities are multiplexed without payload reduction, then complete acknowledgment information is transmitted, but resource utilization deteriorates and high priority channel performance degrades
Solution Approach 1:
The HARQ-ACK payload is segmented by priority levels (first priority and second priority). The payload reduction is applied selectively to the second priority HARQ-ACK bits while preserving the first priority HARQ-ACK bits. This segmentation allows differential treatment of acknowledgment information based on urgency, improving resource utilization without compromising critical feedback reliability.
Solution Approach 2:
Different quality levels are applied to different parts of the HARQ-ACK payload based on priority. First priority HARQ-ACK bits maintain full payload and encoding quality, while second priority bits undergo payload reduction. This local quality differentiation ensures that critical acknowledgments receive full protection while less critical ones consume fewer resources, resolving the contradiction between reliability and resource efficiency.
2Productivity
If payload reduction is applied to low priority HARQ-ACK bits, then resource utilization improves, but information completeness deteriorates
Solution Approach 1:
The payload reduction mechanism is dynamically applied based on priority classification. The system adaptively determines which HARQ-ACK bits to reduce based on their priority level, applying payload reduction only to second priority bits while preserving first priority bits. This dynamic approach allows the system to optimize resource utilization without permanently losing critical information, as the reduction is context-dependent rather than uniform.
Solution Approach 2:
The payload size parameter is changed selectively for second priority HARQ-ACK bits through compression or bundling operations. By modifying the payload parameter only for lower priority information while maintaining full payload for high priority bits, the system achieves better resource utilization without sacrificing essential acknowledgment data, thus resolving the information completeness concern.
3Quantity of substance
If CBG level compression or bundling is applied, then payload size reduces, but processing complexity increases
Solution Approach 1:
The payload reduction through CBG level compression or bundling is performed in advance during the UCI multiplexing process before transmission. By applying the compression/bundling operation preliminarily to second priority HARQ-ACK bits, the system reduces the payload size that needs to be transmitted and processed subsequently, while the processing complexity is confined to the initial compression stage rather than affecting the entire transmission chain.
Data Source
AI summary
A user equipment (UE) is described. The UE includes a processor configured to determine a hybrid automatic repeat request-acknowledgement (HARQ-ACK) pay load reduction for multiplexing HARQ-ACK with different priorities. The processor is also configured to multiplex the HARQ-ACK with different priorities based on the HARQ-ACK payload reduction. The UE also includes transmitting circuitry configured to transmit the multiplexed HARQ-ACK.


