LDPC Code Rate Allocation Across Resource Units Under Interference
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Solution Overview
Problem
Existing LDPC codes have high-density generator matrices that make encoding computationally intensive, and conventional LDPC codes with fixed code rates are inefficient in managing varying signal quality across resource units due to interference, leading to suboptimal performance in communication systems.
Innovation Solution
Implementing systems and methods that allow for multiple code rates and unequal modulation and coding schemes across different resource units in communication systems, using a single mother LDPC code with spawned rates to adapt to varying signal qualities, thereby optimizing performance by tailoring encoding and modulation to the specific conditions of each resource unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional LDPC codes with fixed code rates are used, then encoding complexity is reduced, but performance is suboptimal in managing varying signal quality across resource units
Solution Approach 1:
The patent segments the communication channel into multiple resource units (RUs) and applies different code rates to each RU based on its specific signal quality conditions. This allows the system to divide the transmission into manageable segments, each optimized for its local conditions, thereby improving overall reliability while maintaining manageable encoding complexity through structured segmentation.
Solution Approach 2:
The patent implements local quality by assigning different code rates to different resource units based on their individual signal quality characteristics. Each RU receives a code rate tailored to its specific conditions (e.g., higher code rates for better signal quality, lower code rates for poorer signal quality), enabling the system to optimize performance locally across the frequency spectrum rather than applying a uniform approach.
2Reliability
If multiple code rates and unequal modulation schemes are implemented across resource units, then performance is optimized for varying signal qualities, but encoding complexity increases
Solution Approach 1:
The patent introduces dynamics by making the code rate and modulation scheme adjustable per resource unit based on real-time signal quality conditions. The system dynamically selects appropriate encoding parameters for each RU, allowing it to adapt to changing channel conditions while maintaining a structured framework that prevents encoding complexity from becoming unmanageable through systematic parameter selection.
Solution Approach 2:
The patent utilizes parameter changes by varying code rates and modulation orders across different resource units according to their signal quality. This allows the system to optimize performance by adjusting key transmission parameters (code rate, modulation scheme) locally, achieving better reliability in varying signal conditions while maintaining manageable complexity through standardized parameter sets and selection criteria.
Data Source
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AI summary
In some implementations, an apparatus may include a transmitter (120) and one or more processors (2010). The one or more processors (2010) may identify a plurality of resource units (RUs) (1022) used for transmitting respective data streams within one or more wireless channels. The one or more processors (2010) may determine, based at least on a difference in signal quality between transmissions across the plurality of RUs (1022), respective target code rates for the plurality of RUs (1022). The respective target code rates may be different from each other and different from a base code rate of a low density parity check (LDPC) code. The one or more processors (2010) may encode, by an LDPC encoder (1006) using the LDPC code with the base code rate, the respective data streams to generate respective encoded data streams at the respective target code rates. The transmitter (120) may transmit the respective encoded data streams using the plurality of respective RUs (1022).