Cortex-M Processor Research Articles

Phased array antenna controlled by FPGA-ARM Cortex-M Processor

This paper discusses the architecture of an adaptive transmitting antenna array that allows highly flexible beamsteering. Antenna arrays are used in many digital signal processing applications due to their ability to locate signal sources. The Direction of Arrival (DOA) estimation is a key task of array signal processing, with the Taguchi method and Multiple Signal Classification (MUSIC). Although various algorithms have been developed for DOA estimation, their high complexity prevents their use in real-time applications. In this paper, we design and develop an implementation using Field Programmable Gate Array (FPGA Artix-7), which is the most widely used ARM processor in embedded systems. The antenna array is digitally controlled with the phases synthesized by the Taguchi method.

Applying Lightweight Soft Error Mitigation Techniques to Embedded Mixed Precision Deep Neural Networks

Deep neural networks (DNNs) are being incorporated in resource-constrained IoT devices, which typically rely on reduced memory footprint and low-performance processors. While DNNs’ precision and performance can vary and are essential, it is also vital to deploy trained models that provide high reliability at low cost. To achieve an unyielding reliability and safety level, it is imperative to provide electronic computing systems with appropriate mechanisms to tackle soft errors. This paper, therefore, investigates the relationship between soft errors and model accuracy. In this regard, an extensive soft error assessment of the MobileNet model is conducted considering precision bitwidth variations (2, 4, and 8 bits) running on an Arm Cortex-M processor. In addition, this work promotes the use of a register allocation technique (RAT) that allocates the critical DNN function/layer to a pool of specific general-purpose processor registers. Results obtained from more than 4.5 million fault injections show that RAT gives the best relative performance, memory utilization, and soft error reliability trade-offs w.r.t. a more traditional replication-based approach. Results also show that the MobileNet soft error reliability varies depending on the precision bitwidth of its convolutional layers.

Secure Data of Industrial Internet of Things in a Cement Factory Based on a Blockchain Technology

The Industrial Internet of Things (IIoT) has become a pivotal field of development that can increase the efficiency of real-time collection, recording, analysis, and control of the entire activities of various machines, and can actively enhance quality and reduce costs. The traditional IIoT depends on centralized architectures that are vulnerable to several kinds of cyber-attacks, such as bottlenecks and single points of failure. Blockchain technology has emerged to change these architectures to a decentralized form. In modern industrial settings, blockchain technology is utilized for its ability to provide high levels of security, low computational complexity, P2P communication, transparent logs, and decentralization. The present work proposes the use of a private blockchain mechanism for an industrial application in a cement factory, which offers low power consumption, scalability, and a lightweight security scheme; and which can play an efficient role in controlling access to valuable data generated by sensors and actuators. A low-power ARM Cortex-M processor is utilized due to its efficiency in terms of processing cryptographic algorithms, and this plays an important part in improving the computational execution of the proposed architecture. In addition, instead of proof of work (PoW), our blockchain network uses proof of authentication (PoAh) as a consensus mechanism to ensure secure authentication, scalability, speed, and energy efficiency. Our experimental results show that the proposed framework achieves high levels of security, scalability and ideal performance for smart industrial environments. Moreover, we successfully realized the integration of blockchain technology with the industrial internet of things devices, which provides the blockchain technology features and efficient resistance to common cyber-security attacks.

Cortex-M 계열 프로세서를 이용한 가시광 통신의 VPPM 구현

Visible light communication (VLC) is a short range optical communication technology using light emitting diodes. In this paper, we implement variable pulse position modulation (VPPM) defined in the IEEE 802.15.7 standard with a Cortex-M processor, which is a new modulation scheme for VLC providing a dimming control mechanism for flicker-free optical communication. The synchronization procedure between the transmitter and receiver is not defined clearly in the VPPM standard. In order to synchronize the transmitter and receiver easily, two overhead bits are used including one start bit and one stop bit modulated by on-off keying (OOK). Experimental results under various environmental conditions show that the proposed VPPM can support a seamless 100 Kbps data rate with 10 levels in the dimming control.