GFSK Symbol Decoder Using 3-Symbol Distance Matching
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Solution Overview
Problem
Conventional receivers for Gaussian Frequency Shift Keying (GFSK) communication systems face challenges in decoding symbols effectively due to inter-symbol interference (ISI) and sensitivity to uncertain parameters like phase and frequency offset, making them complex and unsuitable for hand-held devices.
Innovation Solution
A receiver system that uses a discriminator to generate symbols, a lookup table to store bit patterns, and a calculator to calculate distance values between consecutive symbols, allowing for decoding based on information from previous, current, and next symbols, thereby simplifying the decoding process and enhancing robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a near ML decoder is used to mitigate ISI effect, then receiver sensitivity performance is improved, but device complexity increases making it unsuitable for hand-held devices
Solution Approach 1:
The decoder processes symbols in segments of three consecutive symbols (previous, current, and next) rather than requiring complex full-sequence ML decoding. This segmentation allows the use of simpler distance calculation based on pre-stored mapping patterns for each possible 3-bit combination, achieving near-ML performance with reduced computational complexity suitable for hand-held devices.
2Device complexity
If a bitwise discriminator-based decoder is used, then device complexity is reduced, but receiver sensitivity performance deteriorates due to ISI effect
Solution Approach 1:
The decoder uses feedback from previously decoded symbols and anticipated next symbols to improve current symbol decoding. By considering three consecutive symbols and using distance calculation against pre-stored mapping patterns that account for ISI effects, the system achieves better sensitivity performance while maintaining relatively simple device complexity.
3Reliability
If a near ML decoder using Laurent decomposition is used, then receiver sensitivity is improved, but the system becomes sensitive to uncertain parameters such as phase, frequency offset and modulation index
Solution Approach 1:
Instead of using complex Laurent decomposition that requires accurate knowledge of modulation parameters, the patent uses a simpler approach with pre-stored mapping patterns for all possible 3-bit sequences. This disposable-like simplicity in the decoding approach makes the system robust to parameter variations while maintaining improved receiver sensitivity through ISI-aware distance calculation.
Data Source
AI summary
A receiver capable of decoding a symbol based on information on a previous symbol, the symbol and a next symbol in a Gaussian frequency shift keying (GFSK) communication system is provided. The receiver includes a discriminator to generate a symbol for each bit in a bit sequence, a first lookup table (LUT) to store a number of bit patterns and mapping patterns, wherein each of the bit patterns is in the form of a set of consecutive bits in the bit sequence and corresponds to a respective one of the mapping patterns, and wherein each of the mapping patterns includes a set of entries and each of the entries results from an operation of attribute values at a sample time in the waveform of a symbol, a calculator to receive a set of consecutive symbols from the discriminator and calculate a distance value between the set of consecutive symbols and each of the mapping patterns, and a comparator to identify one of the mapping patterns with a minimum distance value by comparing among the distance values from the calculator.