Polar Code Rate Matching Under Circular Buffer Limits
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Solution Overview
Problem
The increasing density of communication devices and data transmission in wireless communication systems poses challenges in efficiently using limited radio resources, particularly in managing high-density nodes and user equipment, and in supporting various services with different requirements while minimizing latency and ensuring reliable data transmission.
Innovation Solution
The implementation of a method for limited buffer rate matching (LBRM) in wireless communication systems, which involves generating coded bits using polar codes and performing rate matching through puncturing or shortening to efficiently store and transmit data in circular buffers, optimizing the use of limited radio resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If polar codes are applied to large-sized information blocks to support different services or higher reliability, then service diversity and reliability are improved, but the codeword may exceed buffer size constraints
Solution Approach 1:
The information block is divided into multiple code blocks, each of which is independently encoded using polar codes. This segmentation allows each code block to fit within buffer size constraints while maintaining the ability to support large-sized information transmission through concatenation of multiple smaller encoded blocks.
Solution Approach 2:
The code block size and code rate are dynamically adjusted based on buffer size constraints and service requirements. By changing these parameters, the system can adapt polar codes to fit within limited buffer space while still supporting large-sized information blocks and different service types.
2Productivity
If the number of UEs and data transmission volume increase to support high-density communication, then communication capacity is improved, but radio resource efficiency deteriorates
Solution Approach 1:
The system dynamically adjusts code block size, code rate, and buffer allocation based on real-time channel conditions, UE density, and traffic requirements. This dynamic adaptation optimizes radio resource efficiency while supporting high-density communication scenarios.
Solution Approach 2:
Communication parameters including code block size, code rate, and buffer size are changed according to service requirements and channel conditions, enabling efficient resource utilization across varying UE densities and traffic loads.
3Adaptability or versatility
If various services with different requirements are supported in a wireless communication system, then service versatility is improved, but system complexity increases
Solution Approach 1:
A universal channel coding framework based on polar codes is designed that can handle different service types (eMBB, mMTC, URLLC) through parameter configuration rather than requiring separate coding schemes. This multi-functionality reduces system complexity while maintaining service versatility.
Solution Approach 2:
The coding parameters and buffer allocation are dynamically configured based on service requirements, allowing a single system to adapt to different service types without requiring complex separate processing paths for each service category.
Data Source
AI summary
A communication device: performs LBRM for storing, in a circular buffer having the length N_IR, N_IR coded bits from among coded bits obtained by performing encoding on the basis of a polar code; performs rate matching on coded bits stored in the circular buffer; and transmits the rate-matched coded bits to another communication device. The communication device stores, in the circular buffer, last N_IR bits from among the coded bits if a code rate is less than or equal to a predetermined value, and, if not, stores first N_IR bits in the circular buffer.