Signal Processing Elementary Cell Architecture for Fast Multiplexing
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Solution Overview
Problem
Conventional signal processing techniques, such as Fast Fourier Transform (FFT), are inadequate in meeting the increasing demands of data communication networks due to high operational complexity and resource requirements, and lack flexibility in adapting to different signal dimensions and processing needs.
Innovation Solution
A novel signal processing method utilizing an elementary cell architecture that reduces multiplication and addition operations, allows for direct and inverse transforms with the same algorithm, and features a flexible algorithm structure that can adapt to various signal dimensions and processing requirements, enabling fast analysis, synthesis, multiplexing, and demultiplexing with minimal resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional signal processing techniques (FFT) are used, then signal processing functionality is provided, but data processing speed is insufficient and operational complexity is high
Solution Approach 1:
The signal processing task is segmented into multiple processing stages with different transform types (DFT, DCT, DST) selected for different frequency bands. This segmentation allows the system to process signals more efficiently by applying the most suitable transform to each segment, reducing overall computational complexity while increasing processing speed.
Solution Approach 2:
The algorithm dynamically selects and switches between different transform types (DFT, DCT, DST) based on the characteristics of the input signal and processing requirements. This dynamic adaptability allows the system to optimize processing speed for different signal types while managing operational complexity through intelligent decision-making rather than fixed complex algorithms.
2Ease of operation
If conventional FFT and IFFT transforms are used, then direct and inverse transforms are achieved, but system resources are excessive
Solution Approach 1:
The patent implements a universal processing framework that handles both direct and inverse transforms using the same algorithmic structure. By making the transform processor multi-functional and adaptable to different transform types (DFT, DCT, DST) and their inverses, the system reduces resource requirements by eliminating the need for separate dedicated hardware or algorithm implementations for each transform pair.
3Ease of manufacture
If fixed algorithm architecture is used, then implementation is simple, but adaptability to different signal dimensions and processing needs is poor
Solution Approach 1:
The algorithm architecture is designed to be dynamic and reconfigurable, allowing it to adapt to different signal dimensions (1D, 2D, 3D, 4D, 5D) and processing requirements. The system can dynamically adjust the number of transform stages, select appropriate transform types for each dimension, and modify processing parameters based on input characteristics, all while maintaining a relatively simple base implementation structure.
Data Source
AI summary
A method and apparatus for fast signal processing is presented. Increase of traffic over data communication networks requires increase of data processing speed. The proposed method is faster than the conventional technique, because it uses less operations of multiplications and additions. The method implements a flexible algorithm architecture based on an elementary cell which is used for both direct and inverse transforms. The method can be implemented for fast analysis and synthesis of different signal types; for fast multiplexing and demultiplexing; and for channel estimation and modeling. The flexible architecture allows: 1) conducting signal analysis according to a certain criterion, and operating on the whole signal or it's part; 2) modifying multiplexed datastream number “on the fly”, splitting and merging groups of datastreams from different sources; 3) splitting a communication channel into a set of subchannels of different bandwidth, organizing data communication in particular subchannels that satisfy certain requirement.