Novel Designs of Fault-Tolerant Nano-Scale Circuits for Digital Signal Processing Using Quantum Dot Technology
Loading...

Date
2026
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier B.V.
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Digital signal processing (DSP) is a crucial engineering field dedicated to the processing and analysis of digital signals. DSP is particularly significant in critical sectors such as telecommunications, medical imaging, and secure communications, where it demands high accuracy, reliability, and real-time performance. In addition, the fault-tolerant (F-T) Arithmetic and Logic Unit (ALU) provides a fundamental building block of DSP architectures, enabling the accurate implementation of arithmetic and logical functions that are essential for advanced computational tasks. However, traditional ALUs were designed using complementary metal-oxide semiconductors (CMOS) and very large-scale integration (VLSI), which led to several challenges, such as high energy consumption, high occupied area, and slow operating speed. These limitations can be effectively addressed through nanotechnology, specifically quantum-dot cellular automata (QCA), which offers high speed, reduces occupying area, and has low power consumption. Accordingly, this paper proposes a QCA-based ALU circuit for DSP applications. The proposed designs integrate an F-T full adder (FA), a QCA-based multiplexer (MUX), and an ALU circuit to enhance performance and efficiency for DSP applications. The validation and verification of all suggested designs are performed using the simulation tool QCADesigner. © 2025 Elsevier B.V.
Description
ORCID
Keywords
Arithmetic and Logic Unit, Digital Signal Processing, Fault-Tolerant, Nanotechnology, QCA
Fields of Science
Citation
WoS Q
Q2
Scopus Q
Q2

OpenCitations Citation Count
N/A
Source
Integration-The VLSI Journal
Volume
106
Issue
Start Page
102572
End Page
PlumX Metrics
Citations
Scopus : 0
Captures
Mendeley Readers : 4
Google Scholar™


