WLAN Signaling Sub-Segment Decoding Without Tail Bits
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Solution Overview
Problem
Current wireless local area network (WLAN) signaling processing methods face inefficiencies in indicating time-frequency resources, leading to increased signaling overhead and reduced decoding performance due to the use of all-zero tail bits and unknown initial states in convolutional coding schemes.
Innovation Solution
The method employs tail-biting convolutional coding without extra all-zero tail bits, setting the initial and final states of the decoder to a reference state sequence known on the receive end, and uses a CRC sequence as a mask for encoding and decoding, reducing signaling overhead and improving decoding performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If all-zero tail bits are used in convolutional coding schemes, then the encoding process is simplified, but signaling overhead increases and decoding performance degrades
Solution Approach 1:
The patent extracts and removes the unnecessary all-zero tail bits from the convolutional coding scheme. By identifying that these tail bits are not essential for the decoding process, the invention eliminates them entirely, thereby reducing signaling overhead while maintaining encoding simplicity through the tail-biting approach where the encoder state returns to the initial state without requiring explicit tail bits.
Solution Approach 2:
Instead of appending all-zero tail bits to terminate the encoder state (conventional approach), the patent inverts the approach by designing the code sequence such that the encoder naturally returns to its initial state at the end of the information sequence. This tail-biting method reverses the traditional tail-bit appending mechanism and achieves state termination without additional bits.
2Ease of manufacture
If all-zero tail bits are used in convolutional coding schemes, then the encoder initialization is simplified, but decoding performance deteriorates due to unknown initial states
Solution Approach 1:
The patent implements feedback mechanisms at the receiver end where the decoded sequence is fed back to verify the encoder final state. The receiver checks whether the encoder returns to the initial state after processing the information sequence, and uses this feedback to confirm correct decoding. This feedback loop ensures decoding reliability without requiring explicit tail bits, as the state return is verified through the decoded output itself.
Solution Approach 2:
The tail-biting convolutional code makes the system self- verifying by design. The encoder state automatically returns to the initial state without external intervention or additional tail bits. The decoding process itself provides the verification mechanism, where successful decoding naturally confirms that the state transition is correct, making the system self-sufficient and eliminating the need for separate initialization verification.
3Loss of information
If tail-biting convolutional coding is used without extra tail bits, then signaling overhead is reduced, but the encoder state management becomes more complex
Solution Approach 1:
The patent changes the fundamental parameter of how encoder state termination is achieved. Instead of using a fixed all-zero state termination with explicit tail bits, the invention modifies the code structure so that the state return to initial condition is an inherent property of the tail-biting code design. This parameter change from explicit termination to inherent state cycling reduces signaling overhead while the state management complexity is handled through pre-computed code sequences.
Solution Approach 2:
The encoder state management is simplified through preliminary action by pre-computing and storing the tail-biting code sequences that guarantee state return to initial condition. Rather than managing complex state transitions in real-time, the system uses pre-prepared code sequences that inherently satisfy the state return requirement, reducing the operational complexity during actual encoding and decoding processes.
Data Source
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AI summary
A method is provided, including: receiving a to-be-decoded signaling sub-segment, where the to-be-decoded signaling sub-segment includes one or more to-be-decoded sequences D0; obtaining a local ID sequence N2 with an N-bit length according to ID information stored on a receive end; for each to-be-decoded sequence D0, setting an initial state and a final state of a decoder to a reference state sequence with a T length and obtaining a decoded sequence D1, where at least some bits in the reference state sequence are identical to some bits in the obtained local ID sequence N2, referred to as a specific reference state sequence in short; and performing processing according to a decoding result.