A Variation-Aware Ternary True Random Number Generator Using Magnetic Tunnel Junction at Subcritical Current Regime

In this article, a variation-aware ternary true random number generator (TTRNG) is proposed and simulated using stochastic switching of the magnetic tunnel junction (MTJ) in the current below critical current and carbon nanotube field-effect transistors (CNTFET). The proposed TTRNG does not need any converters and produces ternary random numbers directly. The stochastic behavior of the MTJ ensures the generation of a truly random sequence. At the same time, the CNTFET threshold voltage adjustability through flat band voltage allows the implementation of ternary logic circuits. A ternary post-processing block is also designed to ensure the equality of the ratio of the numbers generated by the proposed TTRNG, even with the process and voltage variations. Circuit-level simulations performed using the HSPICE tool indicate the correct operation of the proposed TTRNG circuit. Moreover, statistical simulations also authenticate that the ternary sequence generated by the proposed TTRNG is of excellent quality, even in the presence of significant process and voltage variations. The proposed TTRNG can be used in various applications, including cryptography and Monte Carlo simulations. Also, the proposed circuit was redesigned and simulated using FinFET technology as an available technology for fabricating integrated circuits.

Automated summary

This article proposes a variation-aware ternary true random number generator (TTRNG) that utilizes stochastic switching of the magnetic tunnel junction (MTJ) and carbon nanotube field-effect transistors (CNTFET). The TTRNG generates ternary random numbers directly without the need for any converters. The combination of the stochastic behavior of the MTJ and the adjustability of the CNTFET threshold voltage allows for the implementation of ternary logic circuits. The proposed circuit is shown to operate correctly through circuit-level simulations and statistical simulations verify the excellent quality of the ternary sequence generated, even in the presence of process and voltage variations. The TTRNG has potential applications in cryptography and Monte Carlo simulations, and it can be implemented using FinFET technology.