Soft-Decision Audio Decoding for Low-Latency Wireless Continuity
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Solution Overview
Problem
Conventional error detection methods in wireless audio systems result in increased latency and poor granularity, leading to undesirable audio dropouts or muting, especially in harsh RF environments, as they struggle to accurately detect bit errors and maintain audio continuity.
Innovation Solution
A soft decision audio decoding system that generates hard and soft bits to determine whether to decode or mute the digital signal, using techniques like Viterbi algorithms and soft-output decoders to infer errors and maintain audio continuity with improved granularity and low latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional error detection methods (parity checking) are used, then error detection capability is provided, but latency increases and audio continuity deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing syndrome values for all possible error patterns before runtime. During actual error detection, the system simply compares the calculated syndrome with pre-stored values, avoiding time-consuming iterative calculations and significantly reducing latency while maintaining reliable error detection
Solution Approach 2:
The system performs partial error detection by focusing only on the most probable error patterns rather than checking all possible bit combinations. This selective approach detects the majority of practical errors while reducing computational overhead and latency compared to exhaustive error detection methods
2Reliability
If conventional error detection methods are used, then error detection is achieved, but granularity is poor and audio dropouts increase
Solution Approach 1:
The patent segments the error detection process into multiple stages: first detecting whether errors exist using syndrome calculation, then identifying the specific error pattern by comparing with pre-stored syndromes, and finally applying targeted correction. This segmentation enables bit-level precision in error identification and correction, preventing unnecessary audio dropouts that occur with coarse-grained conventional methods
Solution Approach 2:
The system applies local quality by providing different levels of error handling precision for different parts of the data stream. Rather than uniformly treating all data with the same error detection granularity, it identifies and corrects errors at the specific bit level where they occur, maintaining high audio quality by avoiding unnecessary muting or dropout of error-free segments
3Loss of time
If data transmission size is decreased to reduce latency, then latency decreases, but more frequent parity calculations are needed increasing bandwidth cost
Solution Approach 1:
By pre-calculating and storing syndrome values for all possible error patterns during system initialization, the patent eliminates the need for repeated complex parity calculations during data transmission. This preliminary preparation allows rapid error detection with minimal computational overhead, reducing latency without requiring increased bandwidth for frequent re-transmissions
Solution Approach 2:
The system implements self-service through efficient error detection that requires minimal additional processing. The pre-stored syndrome table enables the receiver to autonomously and rapidly identify errors without needing extensive re-transmission protocols or additional bandwidth, making the error detection process self-sufficient and bandwidth-efficient
Data Source
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AI summary
A soft decision audio decoding system for preserving audio continuity in a digital wireless audio receiver is provided that deduces the likelihood of errors in a received digital signal, based on generated hard bits and soft bits. The soft bits may be utilized by a soft audio decoder to determine whether the digital signal should be decoded or muted. The soft bits may be generated based on the detected point and a detected noise power, or by using a soft-output Viterbi algorithm. The value of the soft bits may indicate confidence in the strength of the hard bit generation. The soft decision audio decoding system may infer errors and decode perceptually acceptable audio without requiring error detection, as in conventional systems, as well as have low latency and improved granularity.