Soft Metric Clipping and Non-Linear Mapping for Receiver Efficiency
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Solution Overview
Problem
Digital broadcasting receivers in mobile communication systems face challenges in reducing complexity and power consumption due to the high data rates required for multimedia services, leading to increased receiver complexity and power consumption.
Innovation Solution
The implementation of a non-linear mapping method that clips soft metric values to lower bit representations, allowing for reduced memory usage and power consumption by using a mapper to map demodulated signals to index values with varying resolution levels, and a demapper to convert these index values back to representative soft metric values for decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If soft metric values are stored with high precision (original bit depth), then decoding accuracy is improved, but memory size and power consumption increase
Solution Approach 1:
The patent changes the parameter of soft metric representation from original high-precision bits to quantized index values. The demodulator outputs soft metric values that are quantized to a smaller number of bits (e.g., from 8 bits to 4 bits), creating index values that serve as inputs to the deinterleaver. This parameter transformation reduces memory requirements while maintaining acceptable decoding performance through the mapping relationship between index values and original soft metric ranges.
2Measurement precision
If soft metric values are stored with high precision (original bit depth), then decoding accuracy is improved, but power consumption increases
Solution Approach 1:
The patent transforms soft metric values from high-precision representations to quantized index values with fewer bits. This parameter change reduces the computational burden on subsequent processing stages (deinterleaving, demapping, decoding) and reduces memory access energy, thereby lowering overall power consumption while preserving essential information through the index-to-soft-metric mapping relationship.
3Quantity of substance
If non-linear mapping with varying resolution is used, then memory efficiency is improved, but system complexity increases
Solution Approach 1:
The patent applies local quality by using non-linear mapping where different resolution levels are assigned to different ranges of soft metric values. Critical regions (e.g., near decision boundaries) receive higher resolution quantization, while less critical regions use lower resolution. This localized variation in quantization quality optimizes memory efficiency while maintaining decoding accuracy where it matters most, balancing complexity and performance.
Data Source
AI summary
A broadcasting receiving apparatus and method in a broadcasting system are provided. In a broadcasting receiver, a demodulator demodulates a received broadcasting signal, clips a soft metric value for the demodulated signal to a number of bits, and outputs the clipped soft metric value. A mapper maps the clipped soft metric value to an index value with a resolution inversely proportional to the quantization level of the soft metric value. A deinterleaver deinterleaves the index value and a demapper demaps the deinterleaved index value to a representative value being a soft metric value from a range of soft metric values mapped to the index value. A channel decoder decodes the representative value.