Transport Block Size Quantization for Low-Latency NR Decoding
Find Innovative SolutionsGenerate Solutions
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 issues with transport block size (TBS) calculation leading to high effective code rates greater than 0.95, resulting in decoding errors and increased system latency.
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 to obtain a quantized intermediate number, and determines a transport block size (TBS) to optimize communication efficiency, thereby addressing the limitations of existing systems.
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 dynamic adaptive modulation and coding by selecting different MCS indices based on channel conditions. The base station determines the appropriate modulation order and code rate according to the CQI feedback from the terminal, allowing the system to adapt between high-order modulation (for good channels) and low-order modulation (for poor 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 quality indicators. By adjusting these parameters dynamically according to CQI levels, the system can optimize the balance between transmission rate and error correction capability, achieving both high throughput in good conditions and high reliability in poor conditions
2Reliability
If low-order modulation with lower transmission rate is used, then communication reliability is ensured, but system throughput improvement is restricted
Solution Approach 1:
The system dynamically adjusts modulation and coding parameters based on real-time channel conditions. When channel quality is good (high CQI), the system switches to high-order modulation to maximize throughput. When channel quality deteriorates (low CQI), it switches to low-order modulation to ensure reliability, thus resolving the contradiction
Solution Approach 2:
The patent implements parameter changes by selecting different MCS indices that correspond to different combinations of modulation order and code rate. This allows the system to flexibly adjust between reliability-oriented and throughput-oriented configurations based on channel conditions
3Productivity
If TBS calculation leads to high effective code rates greater than 0.95, then transmission efficiency is improved, but decoding errors increase and system latency increases
Solution Approach 1:
The patent implements feedback mechanisms where the terminal measures channel quality and feeds back CQI information to the base station. The base station uses this feedback to determine appropriate MCS indices and TBS values, avoiding excessively high code rates that would cause decoding failures. This closed-loop feedback system ensures both efficiency and reliability
Solution Approach 2:
The system performs preliminary determination of TBS and MCS index before actual data transmission based on predicted channel conditions from CQI feedback. This preliminary action prevents the selection of inappropriate high code rates that would lead to decoding errors, thus avoiding retransmissions and reducing latency
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.