LDPC Base Graph Selection for Throughput-Energy Tradeoffs
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Solution Overview
Problem
Current wireless communication systems, particularly in 5G NR, face challenges in optimizing LDPC decoder complexity to balance throughput and energy consumption, leading to potential performance degradation and failed transmissions due to the trade-off between computation complexity and energy efficiency.
Innovation Solution
A method where wireless devices select a base graph for LDPC decoders based on configuration parameters such as decoding complexity, device category, and power consumption, allowing for adaptive LDPC coded transmissions and receptions to optimize performance and energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If LDPC decoder computation complexity is increased to improve throughput, then data transmission speed is improved, but energy consumption increases
Solution Approach 1:
The patent implements dynamic base graph selection where the LDPC decoder adapts its configuration based on real-time communication conditions, device capabilities, and channel states. The system can switch between different base graphs (BG1, BG2, etc.) with varying complexity levels, allowing the decoder to operate at high throughput when conditions permit and reduce complexity when energy efficiency is prioritized, thus dynamically balancing the contradiction between productivity and energy consumption
Solution Approach 2:
The patent changes key parameters of the LDPC decoder including base graph selection, number of iterations, and code rate based on communication conditions and device capabilities. By adjusting these parameters, the system can optimize the balance between throughput and energy consumption - for example, using fewer iterations or simpler base graphs when energy efficiency is prioritized, while using more complex configurations when maximum throughput is required
2Use of energy by moving object
If LDPC decoder computation complexity is reduced to decrease energy consumption, then energy efficiency is improved, but throughput decreases
Solution Approach 1:
The system dynamically adjusts decoder complexity based on power management policies and communication conditions. When power saving mode is activated, the system automatically selects base graphs and iteration counts that minimize energy consumption while maintaining acceptable throughput. This dynamic adaptation allows the system to resolve the contradiction by adjusting complexity in real-time based on energy requirements
Solution Approach 2:
The patent employs parameter changes such as selecting different base graphs (BG1 with higher complexity, BG2 with lower complexity), adjusting the number of decoding iterations, and modifying code rates based on power management requirements. These parameter adjustments enable the system to reduce energy consumption when needed while maintaining functional throughput requirements
3Device complexity
If a single base graph is used for all transmissions, then device complexity is reduced, but adaptability to different device categories decreases
Solution Approach 1:
The patent segments the LDPC code design into multiple base graphs (BG1, BG2, BG3, etc.), each optimized for specific device categories and communication scenarios. Instead of using a single universal base graph, the system divides the solution space into specialized segments that can be selectively applied based on device capabilities, thus reducing the complexity burden on individual devices while maintaining overall system adaptability
Solution Approach 2:
Different base graphs are designed with local optimizations tailored to specific device categories (e.g., Category 1, Category 2, Category 3 devices). Each base graph has specific structural properties that are locally optimized for its target device type, allowing the system to maintain low complexity for each individual device category while achieving high adaptability across the entire system through selective base graph assignment
Data Source
AI summary
A first device may select a base graph from a plurality of base graphs based on one or more of (a) a decoding complexity of a second device, (b) a device category of the second device, (c) a capability of the second device, (d) a decoder mode of the second device, (e) a receiver complexity of the second device, (f) a receiver mode of the second device, (g) a power consumption of the second device, (h) a power mode of the second device, or (i) an indication from the second device. The first device may output an LDPC coded transmission to the second device based on the selected base graph.