Practical hardware demonstration of a multi-sensor goal-oriented semantic signal processing and communications network

IF 3.7 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2024-11-07 DOI:10.1016/j.jfranklin.2024.107363

Semih Akkoç , Ayberk Çınar , Berkehan Ercan , Mert Kalfa, Orhan Arikan

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引用次数: 0

Abstract

Recent advancements in machine learning, particularly real-time extraction of rich semantic information, reshape signal processing techniques and related hardware architectures. To address the highly challenging requirements of next-generation signal processing applications in networked platforms, we investigate low-power hardware implementation alternatives for a multi-sensor, goal-oriented semantic communications network. Specifically, we focus on cost-effective Raspberry Pis in a multi-sensor semantic video communication application, showcasing adaptability from traditional CPU/GPU configurations. Additionally, we provide a preliminary investigation on implementing semantic extraction tasks through in-memory computation using memristor arrays to further emphasize the potential future of low-power low-cost semantic signal processing. Hardware demonstrations using Raspberry Pi 4Bs and simulations with in-memory computation architectures offer promising hardware architectures with cost-effective and low-power sensor alternatives to the next-generation semantic signal processing applications and semantic communication systems.

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多传感器目标导向语义信号处理和通信网络的实际硬件演示

机器学习的最新进展，尤其是丰富语义信息的实时提取，重塑了信号处理技术和相关硬件架构。为了满足网络平台中下一代信号处理应用的高难度要求，我们研究了多传感器、面向目标的语义通信网络的低功耗硬件实现替代方案。具体而言，我们将重点放在多传感器语义视频通信应用中的高性价比树莓派（Raspberry Pis）上，展示传统 CPU/GPU 配置的适应性。此外，我们还对利用忆阻器阵列通过内存计算实现语义提取任务进行了初步研究，以进一步强调低功耗、低成本语义信号处理的潜在前景。使用 Raspberry Pi 4B 进行的硬件演示和使用内存计算架构进行的模拟，为下一代语义信号处理应用和语义通信系统提供了具有成本效益和低功耗传感器替代方案的有前途的硬件架构。

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来源期刊

Journal of The Franklin Institute-engineering and Applied Mathematics 工程技术-工程：电子与电气

CiteScore

7.30

自引率

14.60%

发文量

586

审稿时长

6.9 months

期刊介绍： The Journal of The Franklin Institute has an established reputation for publishing high-quality papers in the field of engineering and applied mathematics. Its current focus is on control systems, complex networks and dynamic systems, signal processing and communications and their applications. All submitted papers are peer-reviewed. The Journal will publish original research papers and research review papers of substance. Papers and special focus issues are judged upon possible lasting value, which has been and continues to be the strength of the Journal of The Franklin Institute.