Blind Code Rate Detection Using Incremental Shortening
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In communication scenarios like grant-free transmission, existing technologies face challenges in adapting modulation and coding schemes (MCS) without prior configuration, leading to inefficient data transmission and increased decoding latency.
Innovation Solution
The use of incremental shortening in code structures, such as polar codes and Low Density Parity Check (LDPC) codes, allows for blind detection of code rates, enabling MCS adaptation without explicit signaling, by freezing different numbers of bits in an encoding block to achieve varying code rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the receiver uses many different MCSs to decode received information in grant-free transmission, then the probability of successful decoding is improved, but the decoding latency and complexity increase
Solution Approach 1:
The code structure is segmented into information bits and frozen bits, where frozen bits are predetermined and do not need to be decoded. This segmentation allows the receiver to focus decoding efforts only on information bits, reducing decoding complexity and latency while maintaining successful decoding probability across multiple MCSs
Solution Approach 2:
Frozen bits are predetermined and prepared in advance before transmission. The receiver already knows the values of frozen bits, so no decoding operation is needed for them. This preliminary action eliminates the need to attempt decoding of all bits for multiple MCSs, significantly reducing decoding latency
2Device complexity
If the transmitter and receiver limit communications to only a particular MCS, then decoding complexity is reduced, but adaptability to different channel conditions is worsened
Solution Approach 1:
The code structure with frozen bits is designed to be universal across multiple MCSs. The same code framework can operate at different code rates by simply changing the number of frozen bits, allowing a single decoder design to handle multiple MCSs without increasing complexity, thus achieving both low complexity and high adaptability
Solution Approach 2:
The code rate is adjusted by changing the number of frozen bits rather than changing the entire code structure. This parameter change allows the system to adapt to different channel conditions by selecting appropriate code rates while maintaining the same underlying code structure and decoder complexity
3Measurement precision
If explicit signaling is used to transmit the code rate, then decoding accuracy is improved, but transmission overhead and efficiency are worsened
Solution Approach 1:
The code rate information is embedded within the code structure itself through the number of frozen bits, rather than being transmitted separately as explicit signaling. The receiver can determine the code rate by analyzing the received signal characteristics and the code structure, achieving accurate code rate detection without additional signaling overhead
Data Source
AI summary
Blind detection of code rates for codes with incremental shortening involves determining a decoding code rate for decoding words that are based on codewords of a code that exhibits incremental shortening over a range of code rates. Incremental shortening is a code structure or coding property according to which different numbers of bits in encoding blocks that are to be encoded are set or frozen to a fixed value, to provide the range of code rates. This property enables blind detection of a decoding code rate, without explicit signaling or prior configuration of code rates between a transmitter and a receiver.