Energy-efficient in-memory computing with 8T SRAM for arithmetic operations and signal filtering in UAV communications

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Publicado no:Systems Science & Control Engineering vol. 13, no. 1 (Dec 2025)
Autor principal: Kumar, Sreeja S
Outros Autores: Nayak, Jagadish, Bisni Fahad Mon, Hayajneh, Mohammad, Najah Abu Ali
Publicado em:
Taylor & Francis Ltd.
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022 |a 2164-2583 
024 7 |a 10.1080/21642583.2025.2546828  |2 doi 
035 |a 3285847667 
045 2 |b d20251201  |b d20251231 
100 1 |a Kumar, Sreeja S  |u Electrical & Electronics Engineering, BITS Pilani Dubai Campus Dubai , Dubai , UAE 
245 1 |a Energy-efficient in-memory computing with 8T SRAM for arithmetic operations and signal filtering in UAV communications 
260 |b Taylor & Francis Ltd.  |c Dec 2025 
513 |a Journal Article 
520 3 |a The increasing demand for data-intensive artificial intelligence and machine learning applications has exposed the limitations of traditional Von Neumann architectures, especially in resource-constrained environments like Unmanned Aerial Vehicle (UAV) communication systems. This work introduces an advanced in-memory computing model leveraging an 8T SRAM-based architecture combined with a multi-logic sense amplifier to perform arithmetic operations directly within the memory array. By embedding processing into the memory, this approach significantly reduces data transfer overhead, resulting in lower latency and improved energy efficiency – key requirements for UAV systems. Additionally, a novel lightweight and energy-efficient signal processing method is proposed. This architecture enables real-time signal filtering, effectively minimizing noise and enhancing signal integrity while meeting the compactness and scalability demands of UAV systems. Simulation results demonstrate significant reductions in power consumption and latency across a range of arithmetic operations, with robust performance maintained under varying process, voltage, and temperature conditions. This transformative design offers a practical and efficient solution for next-generation aerial communication technologies, ensuring high-quality communication and efficient data processing in critical UAV applications. 
653 |a Data transfer (computers) 
653 |a Computation 
653 |a Data processing 
653 |a Signal processing 
653 |a Computer architecture 
653 |a Artificial intelligence 
653 |a Arithmetic 
653 |a Communication 
653 |a Signal integrity 
653 |a Unmanned aerial vehicles 
653 |a Sense amplifiers 
653 |a Static random access memory 
653 |a Communications systems 
653 |a Energy efficiency 
653 |a Machine learning 
653 |a Real time 
653 |a Filtration 
700 1 |a Nayak, Jagadish  |u Electrical & Electronics Engineering, BITS Pilani Dubai Campus Dubai , Dubai , UAE 
700 1 |a Bisni Fahad Mon  |u Computer & Network Engineering, United Arab Emirates University , Al Ain , UAE 
700 1 |a Hayajneh, Mohammad  |u Computer & Network Engineering, United Arab Emirates University , Al Ain , UAE 
700 1 |a Najah Abu Ali  |u Computer & Network Engineering, United Arab Emirates University , Al Ain , UAE 
773 0 |t Systems Science & Control Engineering  |g vol. 13, no. 1 (Dec 2025) 
786 0 |d ProQuest  |t Research Library 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3285847667/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3285847667/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch