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 preprocess 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.
A wireless sensor network (WSN) deployed for detection applications has the distinguishing feature that the sensors cooperate to perform the detection task. Therefore, the decoupled and maximum throughput design approaches typically used to design communication networks do not lead to the desired optimal detection performance. Recent work on decentralized detection has addressed the design of media access control (MAC) and routing protocols for detection applications by considering independently the quality of information (QoI), channel state information (CSI), and residual energy information (REI) for each sensor. However, little attention has been given to integrate the three quality measures (QoI, CSI, and REI) in the system design. In this work, we present a cross-layer approach to design a QoI, CSI, and REI-aware transmission control policy (XCP) that coordinates communication between local sensors and the fusion center, in order to maximize the detection performance. We formulate and solve a constrained non-linear optimization problem to find the optimal XCP design variables, for both ALOHA and time-division multiple access (TDMA) sensor networks. We show the detection performance gain compared to the typical decoupled and maximum throughput design approaches, without utilizing additional network resources. We compare ALOHA and TDMA MAC schemes and show the conditions under which each transmission scheme outperforms.
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