Parallel Pseudo-Random Sequence Generation for High-Speed Communication
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Solution Overview
Problem
The generation of pseudo-random sequences in scrambling and descrambling processes is time-consuming, and the time required increases linearly with the length of the sequence, posing challenges for high-speed communication systems like 3GPP LTE and 5G NR.
Innovation Solution
A data processing method and device that generate pseudo-random sequences in parallel and iteratively using recursive formulas for both sequences, allowing for efficient scrambling and descrambling by determining a parallel processing bit width and deriving sub-sequences to reduce generation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pseudo-random sequence generation is performed using traditional sequential methods, then the generation process is simple to implement, but the generation time increases linearly with sequence length
Solution Approach 1:
The patent divides the pseudo-random sequence generation process into multiple parallel segments by deriving separate recursive formulas for different sub-sequences (first sequence and second sequence). Each sub-sequence can be generated independently and simultaneously, breaking the sequential dependency and enabling parallel computation to reduce overall generation time.
Solution Approach 2:
The patent transitions from single-dimension sequential generation to multi-dimension parallel generation by introducing multiple recursive formulas that operate simultaneously. This dimensional expansion allows the system to generate multiple sequence segments in parallel, fundamentally changing the time complexity from linear to logarithmic or constant relative to sequence length.
2Productivity
If parallel processing is used to reduce generation time, then productivity improves, but system complexity increases
Solution Approach 1:
The patent changes the computational parameters by deriving specific recursive formulas that are tailored for parallel execution. By transforming the original sequence generation algorithm into multiple independent recursive relations with specific initial conditions, the system achieves parallelizability without requiring complex hardware modifications, thus managing complexity while improving productivity.
Data Source
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AI summary
A data processing method, device and computer-readable storage medium are disclosed. The method includes: determining a reference value of a number of parallel threads for generating a pseudo-random sequence (S11); obtaining a first sub-sequence of a first sequence according to the first sequence generated by a first sequence generation formula, and deriving a recursive formula of the first sequence (S12); obtaining a first sub-sequence of a second sequence according to the second sequence generated by a second sequence generation formula, and deriving a recursive formula of the second sequence (S13); generating a pseudo-random sequence in parallel and iteratively according to the recursive formula of the first sequence, the recursive formula of the second sequence, the first sub-sequence of the first sequence and the first sub-sequence of the second sequence (S14); and scrambling or descrambling data according to the generated pseudo-random sequence (S15).