Continuous-Time Chaotic Oscillator RNG for High-Rate Randomness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current random number generators (RNGs) face challenges in achieving high throughput and statistical randomness, particularly with increasing data rates in digital communication equipment, and existing designs are complex and noisy, limiting their integration and efficiency.
Innovation Solution
The proposed solution utilizes continuous-time chaotic oscillators to generate random binary data, which are integrated into silicon with less complex and noisy circuits, employing offset and frequency compensation loops to enhance statistical quality and robustness against interference and attacks, and achieving higher data rates without post-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If discrete-time chaotic maps are used for random number generation, then the circuit complexity increases and noise increases, but the implementation is well-established
Solution Approach 1:
The patent replaces discrete-time chaotic maps (mechanical/digital system) with continuous-time chaotic oscillators (analog system). This substitution eliminates the need for successive sample-and-hold stages, multipliers, and numerous capacitors, thereby reducing circuit complexity while maintaining statistical randomness through the natural continuous chaotic behavior.
Solution Approach 2:
The patent extracts and removes the noisy and complex components from the discrete-time implementation, specifically eliminating the successive sample-and-hold stages and multipliers. The essential random number generation function is preserved through the continuous-time oscillator core, leaving only the necessary minimal circuitry.
2Productivity
If traditional RNG designs are used, then the data rate is insufficient for increasing digital communication equipment rates, but the existing designs are simpler
Solution Approach 1:
The patent implements continuous-time chaotic oscillation instead of discrete-time sampling, allowing the random number generation to proceed continuously without interruption. This continuous operation naturally achieves higher data rates as the oscillator runs at GHz frequencies, eliminating the bottleneck of successive sampling stages while keeping the circuit relatively simple.
3Reliability
If noise amplification techniques are used to generate random numbers, then the circuit becomes more complex and noisy, but the randomness quality improves
Solution Approach 1:
The patent converts the natural chaotic behavior (which inherently contains noise-like characteristics) into a beneficial random number source. Instead of amplifying external noise sources, the system generates its own randomness through the deterministic chaotic oscillator, where the sensitive dependence on initial conditions produces unpredictable outputs without requiring noise amplification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution achieves significantly higher data rates and passes rigorous statistical tests, including the NIST test suite, demonstrating improved integration and performance compared to traditional RNGs, with throughput data rates reaching hundreds of Mbps and potential integration at GHz frequencies.
Implementation Method 1
continuous-time chaotic oscillators can be used to realize TRNGs
Data Source
AI summary
Novel random number generation methods and random number generators (RNG)s based on continuous-time chaotic oscillators are presented. Offset and frequency compensation loops are added to maximize the statistical quality of the output sequence and to be robust against parameter variations and attacks. We have verified both numerically and experimentally that, when the one-dimensional section was divided into regions according to distribution, the generated bit streams passed the tests used in both the FIPS-140-2 and the NIST 800-22 statistical test suites without post processing. Numerical and experimental results presented in this innovation not only verify the feasibility of the proposed circuits, but also encourage their use as the core of a high-performance IC RNG as well. In comparison with RNGs based on discrete-time chaotic maps, amplification of a noise source and jittered oscillator sampling, it is seen that RNGs based on continuous-time chaotic oscillators can offer much higher and constant data rates without post-processing. In conclusion, we can deduce that the proposed circuits can be realized in integrated circuits and the use of continuous-time chaos with the proposed innovations is very promising in generating random numbers with very high throughput.