Sequential Distributed Detection in Energy-Constrained Wireless Sensor Networks

Abstract

The recently proposed sequential distributed detector based on level-triggered sampling operates as simple as the decision fusion techniques and at the same time performs as well as the data fusion techniques. Hence, it is well suited for resource-constrained wireless sensor networks. However, in practical cases where sensors observe discrete-time signals, the random overshoot above or below the sampling thresholds considerably degrades the performance of the considered detector. We propose, for systems with stringent energy constraints, a novel approach to tackle this problem by encoding the overshoot into the time delay between the sampling time and the transmission time. Specifically, each sensor computes the local log-likelihood ratio (LLR) and samples it using level-triggered sampling.Then, it transmits a single pulse to the fusion center (FC) after a transmission delay that is proportional to the overshoot, as in pulse position modulation (PPM). The FC, upon receiving a bit decodes the corresponding overshoot and recovers the transmitted LLR value. It then updates the approximate global LLR and compares it with two threshold to either make a decision or to continue the sequential process.We analyze the asymptotic average detection delay performance of the proposed scheme. We then apply the proposed sequential scheme to target detection in wireless sensor networks under the four Swerling fluctuating target models. It is seen that the proposed sequential distributed detector offers significant performance advantage over conventional decision fusion techniques.

Cooperative Sequential Sensing of Radio Transmissions in 5G with Improved Cost-Delay Tradeoff

“…Chin and Chuang [16] applied sequential detection in surveillance sensor networks, in which the sensors periodically reported their local decisions to a fusion center. Yilmaz and Wang [17] proposed a novel approach that the random overshoot above or below the sampling thresholds was proportionately encoded into delay, during which the sensors waited to transmit their processed samples. It is noticed that, in the above works, all sensors were required to make observations, although not all of the observations were necessary [15, 17].…”