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Design of Reversible Binary-to-Gray Code Converter in Quantum-Dot Cellular Automata

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Design and Testing of Reversible Logic

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 577))

Abstract

At nanoscale, for digital systems, the device density and power constraint of the circuit are essential issues. Quantum-dot cellular automata (QCA) is an incipient nanotechnology, which leads to build circuits at nanoscale. It offers various features such as minimal power dissipation, very high-operating frequency, and nanoscale feature size. Besides, reversible computation can lead to the development of low-power systems without loss of information. Thus, reversible QCA logic can provide a powerful and efficient computing platform for digital applications. This paper presents a QCA code converter. Feynman gate is used as a fundamental building block to perform the proposed design of code converter. QCADesigner version 2.0.3 is used to validate the accuracy of the proposed circuit. QCAPro, a very widespread power estimator simulation engine, is applied to estimate the power depletion of the proposed circuit.

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References

  1. Haron NZ, Hamdioui S (2008) Why is CMOS scaling coming to an END? In: 3rd IEEE international design and test workshop (IDT), pp 98–103

    Google Scholar 

  2. Bondy PK (2002) Moore’s law governs the silicon revolution. In: Proceedings of the IEEE, pp 78–81

    Google Scholar 

  3. Landauer R (1961) Irreversibility and heat generation in computing process. IBM J Res Dev 5(3):183–191

    Google Scholar 

  4. ITRS, International Technology Roadmap for Semiconductors 2013 Update Technical Report. Available www.itrs.net

  5. Niamat M, Panuganti S, Raviraj T (2010) QCA design and implementation of SRAM based FPGA configurable logic block. In: 53rd IEEE international midwest symposium on circuits and systems (MWSCAS), pp 837–840

    Google Scholar 

  6. Zhang R, Walus K, Wang W, Jullien GA (2004) A method of majority logic reduction for quantum cellular automata. IEEE Trans Nanotechnol 3(4):443–450

    Article  Google Scholar 

  7. Orlov AO, Amlani I, Bernstein GH, Lent CS, Snider GL (1997) Realization of a functional cell for quantum-dot cellular automata. Science 277(5328):928–930

    Article  Google Scholar 

  8. Bennett CH (1973) Logical reversibility of computation. IBM J Res Dev 17(6):525–532

    Article  MathSciNet  Google Scholar 

  9. Wille R, Soeken M, Miller M, Drechsler R (2014) Trading off circuit lines and gate costs in the synthesis of reversible logic. Integr VLSI J 47(2):284–294

    Article  Google Scholar 

  10. Sasamal TN, Mohan A, Singh AK (2018) Efficient design of reversible logic ALU using coplanar quantum-dot cellular automata. J Circuits Syst Comput 1–19

    Google Scholar 

  11. Das JC, De D (2016) Novel low power reversible binary incrementer design using quantum-dot cellular automata. Microprocess Microsyst 42:10–23

    Article  Google Scholar 

  12. Debnath B (2016) Reversible logic-based image steganography using quantum dot cellular automata for secure nanocommunication. IET Circuits Devices Syst 1–10

    Google Scholar 

  13. Das JC, De D (2016) User authentication based on quantum-dot cellular automata using reversible logic for secure nanocommunication. Arab J Sci Eng 41(3):773–784

    Article  MathSciNet  Google Scholar 

  14. Das JC, De D (2016) Quantum dot-cellular automata based reversible low power parity generator and parity checker design for nanocommunication. Front Inf Technol Electron Eng 17(3) 224–236

    Article  Google Scholar 

  15. Bhoi (2017) Design and evaluation of an efficient parity-preserving reversible QCA gate with online testability. Cogent Eng 1–18

    Google Scholar 

  16. Ahmad PZ (2017) A novel reversible logic gate and its systematic approach to implement cost-efficient arithmetic logic circuits using QCA. Data Brief 15:701–708

    Article  Google Scholar 

  17. Chabi AM (2017) Towards ultra-efficient QCA reversible circuits. Microprocess Microsyst 49:127–138

    Article  Google Scholar 

  18. Kamaraj A, Ramya S (2014) Design of router using reversible logic in quantum cellular automata. In: International conference on communication and network technologies (ICCNT), pp 249–253

    Google Scholar 

  19. Lent CS (1993) Quantum cellular automata. Nanotechnology 4(1):49–57

    Article  Google Scholar 

  20. Tougaw PD, Lent CS (1994) Logical devices implemented using quantum cellular automata. J Appl Phys 75(3):1818–1825

    Article  Google Scholar 

  21. Lent CS (2003) Clocked molecular quantum-dot cellular automata. IEEE Trans Electron Devices

    Google Scholar 

  22. Tang R, Zhang F, Kim YB (2005) Quantum-dot cellular automata SPICE macro model. In: Proceedings of the 15th ACM great lakes symposium on VLSI, pp 108–111

    Google Scholar 

  23. Momenzadeh M, Huang J, Lombardi F (2008) Design and test of digital circuits by quantum-dot cellular automata. Artech House, pp 37–67

    Google Scholar 

  24. Angizi S, Sarmadi S, Sayedsalehi S, Navi K (2015) Design and evaluation of new majority gate-based RAM cell in quantum-dot cellular automata. Microelectron J 46(1):43–51

    Article  Google Scholar 

  25. Walus K, Dysart TJ, Jullien GA, Budiman RA (2004) QCADesigner: a rapid design and simulation tool for quantum-dot cellular automata. IEEE Trans. Nanotechnol 3(1):26–31

    Article  Google Scholar 

  26. Biswas PK, Bahar AN, Habib MA, Al-Shafi MA (2017) Efficient design of Feynman and Toffoli gate in quantum dot cellular automata (QCA) with energy dissipation analysis. Nanosci Nanotechnol 7(2):27–33

    Google Scholar 

  27. Srivastava S (2011) QCAPro – an error-power estimation tool for QCA circuit design. In: International symposium of circuits and systems (ISCAS), pp 2377–2380

    Google Scholar 

  28. Das JC, De D (2015) IETE J. Res. 1

    Google Scholar 

  29. Neeraj KM, Subodh W, Singh VK (2016) In: Proceedings of the 4th international conference on frontiers in intelligent computing: theory and applications (FICTA)

    Google Scholar 

  30. Javeed IR, Banday MT (2011) Efficient design of reversible code converters using quantum dot cellular automata. J Nano- Electron Phys 1–8

    Google Scholar 

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Correspondence to I. Gassoumi .

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Gassoumi, I., Touil, L., Ouni, B. (2020). Design of Reversible Binary-to-Gray Code Converter in Quantum-Dot Cellular Automata. In: Singh, A., Fujita, M., Mohan, A. (eds) Design and Testing of Reversible Logic. Lecture Notes in Electrical Engineering, vol 577. Springer, Singapore. https://doi.org/10.1007/978-981-13-8821-7_14

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  • DOI: https://doi.org/10.1007/978-981-13-8821-7_14

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  • Online ISBN: 978-981-13-8821-7

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