White Gaussian Noise Generator Using Fast Walsh Transform
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Solution Overview
Problem
Existing methods for generating white Gaussian noise in wireless communications are computationally intensive, especially for wideband waveforms, due to the complexity of transcendental mathematical functions required, which makes them inefficient for high-bandwidth applications.
Innovation Solution
A wireless communications device equipped with a pseudorandom number generator and a fast Walsh transform module that converts uniform pseudorandom numbers into Gaussian distributed noise using straightforward addition and subtraction operations, suitable for hardware implementation in a field-programmable gate array (FPGA), allowing for efficient generation of white Gaussian noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transcendental mathematical functions are used to generate white Gaussian noise, then the noise generation accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent transforms the generation of Gaussian distributed noise from a direct mathematical function approach to an indirect transformation approach. Specifically, it generates uniformly distributed random numbers first, then applies a transformation function to convert them into Gaussian distributed noise. This parameter transformation strategy changes the distribution characteristics from uniform to Gaussian, achieving accurate noise generation while avoiding complex transcendental functions.
2Adaptability or versatility
If software implementation on microprocessors is used, then the flexibility is improved, but the processing speed decreases
Solution Approach 1:
The patent replaces the software-based microprocessor implementation with a hardware-based field-programmable gate array (FPGA) implementation. This substitution of the execution medium from software to hardware significantly improves processing speed while maintaining the flexibility of FPGA reconfigurability. The transformation function and random number generation logic are implemented as hardware circuits, enabling parallel processing and eliminating software interpretation overhead.
3Productivity
If the signal bandwidth increases, then the communication capacity is improved, but the computational load for noise generation increases
Solution Approach 1:
The patent segments the noise generation process into independent parallel components that can be simultaneously executed. The transformation function is divided into multiple parallel processing stages, and the random number generation is organized into parallel streams. This segmentation allows the system to handle wider signal bandwidths by distributing the computational load across multiple parallel operations, thereby maintaining constant computational complexity per unit bandwidth.
Data Source
AI summary
A wireless communications device may include a wireless transmitter, a modulator connected to the wireless transmitter, and a white Gaussian noise generator connected to the modulator. The white Gaussian noise generator may include at least one pseudorandom number generator, and a fast Walsh transform module for generating white Gaussian noise based upon the pseudorandom numbers.