Energy-Efficient Code Conversion Using Quantum-Dot Nano-Architectures for Internet of Things (IoT) Applications
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Date
2026
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Publisher
Springer
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Abstract
Internet of Things (IoT) is a developing technological trend in which common real-world objects are connected with technologies of sensors, actuators, and communication units, allowing data collection, sharing, and processing via the Internet. One of the important circuits in IoT systems is code converter circuits, which are critical components in data formatting, arithmetic processing, and error-resistant processing in these systems, and hence, have a direct influence on performance and energy resources. However, complementary metal-oxide-semiconductor-based realizations of these converters suffer important drawbacks, including high occupied area, increased power dissipation, propagation delays, and longer latency, and are not suitable in ultra-compact and energy-constrained IoT devices. To overcome these challenges, emerging technologies like the quantum-dot cellular automata (QCA) are offering new alternatives, featuring ultra-low power consumption, low area, and high processing speed, which would make QCA technologies suitable for next-generation IoT applications. This paper proposes high-density and power-efficient bidirectional code converter circuits (BCD to Excess-3-B2X3C and Excess-3 to BCD-X3B2C converters) utilizing QCA technology. In addition, significant improvements are demonstrated by the comparative evaluations, which include an improvement of 7.89% in cells, a reduction of 25% in area-delay cost (A x D2), and a 43.75% in figure of merit (FoM), respectively. Additionally, QCADesigner and QCAPro simulation and power analysis indicate that the switching energy is generally low throughout a wide variety of tunneling energies. The presented QCA-based single layer is more scalable than current designs, which makes it suitable for future IoT integration.
Description
Chugh, Hemanshi/0000-0002-9324-4383
ORCID
Keywords
Quantum Dot, Code Converters, Internet of Things (IoT), Low Power Design, Qcadesigner-E
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WoS Q
Q2
Scopus Q
Q1

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N/A
Source
Journal of Supercomputing
Volume
82
Issue
2
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Citations
Scopus : 0
