LDPC Mapping Patterns for DVB-NGH Shaping Gain
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Solution Overview
Problem
The DVB-NGH system faces challenges in achieving maximum shaping gain due to the direct adaptation of non-uniform mapping patterns from the DVB-T2 system, particularly with the 64k mode, L1 signaling information, and MIMO profiles, which results in suboptimal error correction capabilities and increased C/N ratios.
Innovation Solution
The implementation of a transmission device and method that allows for different non-uniform mapping patterns based on LDPC code lengths and coding rates, specifically defining new patterns for the 64k mode, L1 signaling information, and MIMO profiles to optimize shaping gain, while also considering error correction capabilities and interference effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If non-uniform mapping patterns from DVB-T2 system are directly adapted to DVB-NGH system, then implementation simplicity is improved, but shaping gain achievement deteriorates
Solution Approach 1:
The patent applies local quality by defining different non-uniform mapping patterns tailored to specific LDPC code lengths (16k, 64k) and transmission modes (SISO, MISO, MIMO). Instead of using a single universal mapping pattern, the system optimizes mapping characteristics locally for each configuration to achieve maximum shaping gain while maintaining implementation feasibility within the DVB-NGH framework.
Solution Approach 2:
The patent implements parameter changes by modifying the mapping patterns based on LDPC code length and transmission mode parameters. The mapping patterns are adjusted to match the specific characteristics of 16k vs 64k LDPC codes and SISO vs MIMO configurations, thereby optimizing shaping gain for each parameter combination while maintaining system-wide compatibility.
2Device complexity
If same non-uniform mapping pattern is used for different LDPC code lengths, then system complexity is reduced, but error correction capability deteriorates
Solution Approach 1:
The patent defines distinct non-uniform mapping patterns for 16k and 64k LDPC code lengths, optimizing each pattern to match the error correction characteristics of its corresponding code length. This local optimization ensures that each mapping pattern maximizes shaping gain for its specific LDPC configuration without compromising error correction capability.
Solution Approach 2:
The patent segments the mapping pattern definition into separate configurations for different LDPC code lengths (16k, 64k) and transmission modes. By dividing the overall mapping strategy into specialized segments, the system achieves optimal error correction performance for each code length while maintaining manageable complexity through standardized segmentation approaches.
3Ease of manufacture
If uniform mapping pattern is used across all transmission modes, then implementation simplicity is improved, but transmission efficiency deteriorates
Solution Approach 1:
The patent optimizes mapping patterns locally for SISO, MISO, and MIMO transmission modes by considering the specific interference characteristics and signal-to-noise ratio requirements of each mode. This localized optimization improves transmission efficiency for each mode while maintaining reasonable implementation complexity through systematic pattern design.
Solution Approach 2:
The patent introduces dynamic adaptation of mapping patterns based on transmission mode selection. The system dynamically selects appropriate non-uniform mapping patterns according to whether SISO, MISO, or MIMO mode is active, thereby optimizing transmission efficiency for each operational context while maintaining a finite set of predefined patterns for implementation efficiency.
4Productivity
If non-uniform mapping patterns are optimized for each transmission mode, then transmission efficiency is improved, but system complexity increases
Solution Approach 1:
The patent achieves local optimization of mapping patterns for SISO, MISO, and MIMO modes while controlling overall system complexity through a finite set of predefined patterns. Each mode has its optimized pattern, but the total number of patterns remains manageable, and selection is based on simple mode identification rather than complex adaptive algorithms.
Data Source
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AI summary
An FEC coder in a transmission device according to an exemplary embodiment of the present disclosure performs BCH coding and LDPC coding based on whether a code length of the LDPC coding is a 16k mode or a 64k mode. A mapper performs mapping in an I-Q coordinate to perform conversion into an FEC block, and outputs pieces of mapping data (cells). The mapper defines different non-uniform mapping patterns with respect to different code lengths even an identical coding rate is used. This configuration improves a shaping gain for different error correction code lengths in a transmission technology in which modulation of the non-uniform mapping pattern is used.