An Ultra-Low Power Multivibrator-Based Wake-up Receiver for Wireless Sensor Networks

Abstract

In recent years wireless sensor networks (WSNs) have gained significant attention because of their implementation in many different fields. As the nodes in WSNs are typically battery-powered, their lifetime is mainly limited by the sensor nodes power consumption. A typical energy-saving solution consists in implementing wake-up receivers (WuRxs), which are responsible for the sensor node activation only when required. In this work an ultra-low power multivibrator-based WuRx concept is proposed. The WuRx is composed of several input-triggered multivibrators, which generate pulses of fixed duration. These pulses are compared to the input signal through logic gates, which are predefined according to the wake-up call. The sensor node is activated if the codes match. An implementation in TSMC-180nm CMOS process is proposed and simulated. The WuRx consumes 0.8µW when detecting a 6ms wake-up call signal, and 58.4pW when in idle mode.

Nano-Power Monostable-Based Wake-Up Mechanism for Wireless Sensor Networks

“…The switch circuit also avoids floating gate at the input of the monostables. As reported in the introduction, this WuRx concept has been proposed in our previous work [15]. The novelty of this work is the simplification of the monostable circuit.…”

“…The WuC can be based on radio, optical and acoustic signals depending on the medium of transmission. In our previous work, we proposed an ultra-low power WuRx based on a NOR-based monostable multivibrator topology for acoustic applications [15]. In this article we report a simpler and less power consuming monostable circuit, composed of only two transistors, two resistors and a capacitor.…”

“…In this article we report a simpler and less power consuming monostable circuit, composed of only two transistors, two resistors and a capacitor. Instead the monostable in [15] is composed of six transistors, one capacitor and one resistor. The proposed circuit is verified by simulations, by considering an acoustic WuC signal with carrier frequency of 40kHz.…”

A Review on Congestion Mitigation Techniques in Ultra-Dense Wireless Sensor Networks: State-of-the-Art Future Emerging Artificial Intelligence-Based Solutions

“…track sound waves emanating from submarines in the Pacific and Atlantic oceans. WSNs are interdisciplinary technologies that combine the comprehensive techniques of wireless communications, pervasive computing, networking, and signal processing [6]. WSNs have evolved continuously and incrementally since the 1960s [6].…”

“…WSNs are interdisciplinary technologies that combine the comprehensive techniques of wireless communications, pervasive computing, networking, and signal processing [6]. WSNs have evolved continuously and incrementally since the 1960s [6]. However, the Defense Advanced Research Projects Agency (DARPA) launched a brand-new initiative called Distributed Sensor Networks (DSNs) in the 1970s [7].…”