Transport Block Size Quantization for Reliable URLLC Scheduling
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Solution Overview
Problem
Current LTE and NR communication systems fail to effectively support low-latency and high-reliability communication, particularly in ultra-reliable and low-latency communication (URLLC) scenarios, due to limitations in the MCS table that lead to excessive system latency and instability.
Innovation Solution
A data communication processing method and device that acquires a modulation order and target code rate, calculates an intermediate number of information bits, quantizes these bits, and determines a transport block size (TBS) to optimize communication efficiency, thereby addressing the limitations of the existing MCS table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-order modulation with higher transmission rate is used, then system throughput is improved, but communication reliability deteriorates in deep fading channels
Solution Approach 1:
The patent implements adaptive modulation and coding by dynamically selecting different MCS indices based on channel conditions. The terminal device adjusts the modulation order and code rate according to downlink channel quality indicators, enabling the system to switch between high-order modulation (for good channels) and low-order modulation with higher redundancy (for deep fading channels), thus resolving the contradiction between throughput and reliability
Solution Approach 2:
The patent changes the parameters of modulation order and code rate based on channel state. By adjusting these parameters dynamically, the system can optimize the balance between transmission rate and reliability for different channel conditions, allowing high throughput when channel is good and high reliability when channel is poor
2Reliability
If low-order modulation with larger redundancy is used, then communication reliability is ensured, but system throughput improvement is restricted in high signal-to-noise ratio channels
Solution Approach 1:
The system dynamically adapts the modulation and coding parameters based on real-time channel quality feedback. When the channel quality is high (high signal-to-noise ratio), the system switches to high-order modulation with lower redundancy to maximize throughput. When channel quality degrades, it transitions to low-order modulation with higher redundancy to ensure reliability, thus resolving the contradiction
Solution Approach 2:
The patent adjusts modulation order and code rate parameters dynamically according to channel conditions. In high signal-to-noise ratio environments, the system increases modulation order and decreases redundancy to boost throughput. In poor channel conditions, it reverses these adjustments to maintain reliability, effectively resolving the throughput-reliability trade-off
3Adaptability or versatility
If the MCS table is used in current LTE or NR systems, then communication is supported, but low-latency and high-reliability communication requirements for URLLC cannot be met
Solution Approach 1:
The patent segments the MCS table into multiple versions (first MCS table and second MCS table) with different characteristics. The first MCS table is optimized for general communication scenarios, while the second MCS table is specifically designed for URLLC scenarios with parameters optimized for low latency and high reliability. This segmentation allows the system to select the appropriate table based on service requirements
Solution Approach 2:
The patent applies different MCS table configurations for different communication scenarios. The second MCS table has local optimizations specifically tailored for URLLC requirements, such as adjusted modulation orders and code rates that prioritize reliability and low latency over maximum throughput. This local quality approach enables specialized optimization for critical communication scenarios
Data Source
AI summary
Provided are a data communication processing method and device. The method includes: acquiring a modulation order and a target code rate; calculating an intermediate number Ninfo of information bits at least according to a total number of resource elements, the modulation order and the target code rate; quantizing the intermediate number Ninfo of the information bits to obtain the quantized intermediate number N′info; determining a transport block size (TBS) according to the quantized intermediate number N′info.