RSSI-based parameter estimation for rician fading environments on wireless sensor nodes

The communication channels in many practical scenarios, e.g., in industrial indoor environments can be modeled through Rician fading. Such a channel is characterized by its mean pathloss and Rician K factor. The computation of these parameters is essential for optimum power allocation, especially for wireless sensor networks consisting of energy-constrained battery-driven nodes. The most promising methods for estimating the K factor in simple transceivers are based on the statistical moments of the received power or amplitude. The existing energy-based methods are limited in accuracy, whereas the amplitude-based methods are computationally complex for implementation on simple hardware. In this work, a novel, low-complexity method to estimate the Rician K factor in narrowband channels is proposed. The method is based on the usually available received signal strength indicator (RSSI). A simple scheme is also presented to calculate the optimal transmit power using the estimated mean pathloss and the K factor. The calculated transmit power ensures a desired outage probability at the receiver. The K factor and mean pathloss estimation as well as the transmit power calculation methods are practically implemented on simple hardware nodes. The effectiveness of the methods is proven through simulations and experimental results.