LDPC Code Structure for Negative-SNR Terrestrial Cloud Broadcast
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Solution Overview
Problem
Current terrestrial TV broadcasting systems face co-channel interference, leading to inefficient spectrum reuse and the occurrence of 'white space,' which necessitates a technology that can operate in negative Signal to Noise Ratio (SNR) environments and improve transmission capacity and robustness in reception.
Innovation Solution
The development of an LDPC encoder and decoder that uses a parity check matrix structure combining a first parity check matrix for a higher code rate with a second parity check matrix for a lower code rate, incorporating a dual diagonal matrix, identity matrix, and zero matrix to encode and decode input information efficiently in a terrestrial cloud broadcast system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a conventional LDPC code is used for terrestrial cloud broadcast, then the system can operate in typical SNR environments, but it fails to provide sufficient error correction performance in negative SNR environments
Solution Approach 1:
The patent modifies the parity check matrix structure by incorporating a dual diagonal matrix pattern with specific mathematical parameters (e.g., powers of 2 for column shifts) to optimize error correction performance in negative SNR environments. This parameter optimization enables the LDPC code to achieve reliable communication where conventional codes fail.
Solution Approach 2:
The parity check matrix is segmented into distinct functional blocks including identity matrices, dual diagonal matrices, and zero matrices. This segmentation allows each block to serve specific error correction functions, with the dual diagonal matrix specifically targeting the challenges of negative SNR environments.
2Reliability
If the parity check matrix structure is optimized for better error correction performance, then the code complexity increases
Solution Approach 1:
The patent optimizes the dual diagonal matrix parameters (such as the exponent values in powers of 2) to achieve the best error correction performance with minimal complexity. By carefully selecting these parameters, the system achieves high reliability without proportionally increasing implementation complexity.
Solution Approach 2:
The dual diagonal matrix structure serves multiple functions simultaneously: it provides error correction capability, enables systematic encoding, and maintains compatibility with existing LDPC decoding algorithms. This multi-functionality reduces the need for additional complex components.
3Productivity
If frequency reuse is implemented in terrestrial broadcasting to improve spectrum efficiency, then co-channel interference increases
Solution Approach 1:
The patent converts the harmful effect of co-channel interference into a manageable challenge by designing an LDPC code specifically optimized for negative SNR conditions. The dual diagonal matrix structure is engineered to exploit the statistical properties of interference-limited channels, transforming the interference problem into an opportunity for optimized error correction.
Solution Approach 2:
The LDPC code with dual diagonal matrix structure provides beforehand cushioning against co-channel interference by pre-establishing robust error correction capability. The code is designed in advance to handle the expected interference levels, allowing frequency reuse without requiring additional interference mitigation infrastructure.
Data Source
AI summary
Provided is an LDPC (Low Density Parity Check) code for terrestrial cloud broadcast. A method of encoding input information based on an LDPC (Low Density Parity Check) includes receiving information and encoding the input information with an LDPC codeword using a parity check matrix, wherein the parity check matrix may have a structure obtained by combining a first parity check matrix for an LDPC code having a higher code rate than a reference value with a second parity check matrix for an LDPC code having a lower code rate than the reference value.