An Adaptive Amplifier for Wireless Sensor Network Applications - Embedded.com

An Adaptive Amplifier for Wireless Sensor Network Applications

The advances in electronics have enabled the development of low cost, low power, and multifunctional wireless sensor nodes that consist of sensing, data processing, and communication components. These small sensor nodes can be installed in a designated area to form a wireless network for performing specific functions.

Usually, a host computer collects data from the sensors and carries out different actions depending on the particular purpose of the system. A broad range of applications has been proposed for this kind of systems such as industrial sensor networks, environmental monitoring, home automation, and medical care.

However, in a number of applications, the nodes operate in harsh environments, under the action of a several agents that could potentially deteriorate their performances. If the application is critical, reliable operation of the node can require characteristics of safe operation, adaptation to a changing environment, or ability for compensating degradations in its own circuitry. For achieving this purpose, two related characteristics are necessary: fault detection and circuit self- adaptation.

The fault detection characteristic could be constrained by the low power operation of the node, which could make the use of dedicated test circuitry inconvenient for performing built-in self-test. Instead, a software-based self-test (SBST) strategy arises as an effective alternative that can provide infield testing capabilities with very low area and performance overhead.

Providing adaptive characteristics to the node requires configurable hardware sections and a reconfiguration methodology. Evolvable hardware (EHW) is a methodology that offers self-adaptation by combining reconfigurable hardwarewith evolutionary algorithms.

In EHW, the designer establishes performance goals and usually a genetic algorithm searches for the possible hardware configurations for reaching them. In this way, EHW offers an alternative to traditional fault tolerant schemes. Additionally, even if EHW does not always guarantee that a complete functionality can be restored, it allows maintaining the system operation with graceful degradation.

In this paper, we focus our efforts in the development of an adaptive amplifier embedded in the microcontroller that is part of the node. We implement the amplifier on a an 8051-based PSoC1 device from Cypress with the appropriate analog reconfigurable sections.

One of the goals of our work is the development of a very low cost SBST strategy for the analog configurable sections. The other goal is the development of an evolvable hardware (EHW) strategy that uses a GA-based reconfiguration strategy, which runs on the host computer. In this way, the amplifier maintains its targeted functional parameters between limits established by the user, without direct human intervention.

The system presents a target gain that has to be maintained without direct human intervention despite the presence of faults. In addition, its bandwidth must be as large as possible. The system is composed of a software-based built-in self-test scheme implemented in the node that checks all the available gains in the amplifiers, a reconfigurable amplifier, and a genetic algorithm (GA) for reconfiguring the node resources that runs on a host computer.

Particularly suitable for microcontrollers, an SBST strategy utilizes the existing processing core to perform a self-test of the analog and digital components in a node.Providing adaptive characteristics to the node requires configurable hardware sections and a reconfiguration methodology. Evolvable hardware (EHW) is a methodology that offers self-adaptation by combining reconfigurable hardwarewith evolutionary algorithms.

The performance evaluation of the scheme presented is done by using four different types of fault models in the amplifier gains. The fault simulation resultsshow that GA finds the target gain with low error, maintains the bandwidth above the minimum tolerable bandwidth, and presents a runtime lower than exhaustive search method.

To read more of this external content, download the complete paper from the author archives at Hindawi. 

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