Detection using intermittent observations for passive wireless sensors

Abstract

Passive wireless sensors have emerged as a new technology to measure multiple phenomena in our daily life. Passive sensors require no power source, and therefore their application domains are numerous, including health care, infrastructure protection, and national security. The deployment of passive wireless sensors and their readers has changed how detection needs to be performed. Passive sensors cannot pre-process the measurements as they have limited computational power. Therefore, no local decision is taken. Also, the reader polls the information from multiple sensors at the same time, and this causes collisions and hence packet drops and delays. Detectors designed without considering the properties of the communication channel have degraded performance. Therefore, analysis is required to quantify the degradation and take the necessary remedy action. In this paper, we study the effect of sensor-reader channel imperfection on the local detection performance of the reader, assuming no data pre-processing at the passive sensor.We consider the case of a single sensor-reader communication over a Bernoulli communication channel. We formulate the detector performance and compare with the ideal case. We present the problem of DC level detection in white Gaussian noise, as a case study. Finally, we propose a heuristic approach to restore the original detector performance working with non-ideal channel, with the cost of increasing the delay for detection.