A Joint Fusion, Power Allocation and Delay Optimization Approach for Wireless Sensor Networks

In this paper, we consider the cross-layer optimization of wireless sensor networks (WSNs) under the constraints of total energy consumption and transmission delay. A Gaussian WSN with time division multiple access (TDMA) media access control (MAC) layer protocol is used here. The sensed data are contaminated by sensor noise, before converting to digital bits by quantization. The digital bits are transmitted through a noisy wireless communication channel. In fusing the sensed information from individual sensors, a fusion rule is employed to recover the original data. Least square error (LSE) rule is considered here due to its low computation complexity. The mean distortion level is employed to measure the system performance. Since the battery life is limited and the data delay is crucial, we propose here to optimize the transmission power allocation strategy and the delay of each node in order to minimize the mean distortion of the measured information. Using computer simulations, the proposed adaptive approach is shown to provide an effective sensing in terms of performance and energy consumption.