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Novel optimized ultra-dense 1-bit magnitude comparator design in quantum-dot cellular automata technology based on MV32 gate

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Abstract

Quantum-dot cellular automata (QCA) are based on the nanoscale and used as an alternative for Complementary Metal Oxide (CMOS) semiconductor technology. The main feature that attracts researchers in the VLSI domain of QCA is the ultra-dense structures with less power consumption and fewer transistors count. This paper presents a low energy dissipation 1-bit magnitude comparator using modified MV32 gates with minimum area. The simulation results of the proposed design have a value of 2.05 meV as total energy dissipation and 0.198 meV as average energy dissipation per cycle. Being at the nanoscale, the possibility of defects must be explored and analyzed. Therefore, the single missing cell analysis for the MV32 gate is carried out and presented in this paper. The hardware description language model is developed to analyze the faults caused by the single missing cell defects in the MV32 gate. At last, the proposed comparator is analyzed under the single missing cell defect to prove its fault tolerance.

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Data availability statement

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, National University of Singapore, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore

    Nehru Kandasamy

  2. Department of Electronics and Communication Engineering, Institute of Technology, Nirma University, Ahmedabad, India

    Vaishali Dhare

  3. Department of Electrical Electronics and Communication Engineering, GITAM University, Bengaluru, India

    Nagarjuna Telagam

Authors
  1. Nehru Kandasamy
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  2. Vaishali Dhare
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  3. Nagarjuna Telagam
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Correspondence to Vaishali Dhare.

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Kandasamy, N., Dhare, V. & Telagam, N. Novel optimized ultra-dense 1-bit magnitude comparator design in quantum-dot cellular automata technology based on MV32 gate. J Supercomput 78, 18666–18690 (2022). https://doi.org/10.1007/s11227-022-04604-2

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  • DOI: https://doi.org/10.1007/s11227-022-04604-2

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