Iterative path-loss exponent estimation-based positioning scheme in WSNs

Abstract

In wireless sensor networks, the positioning scheme using the received signal strength (RSS) has been widely considered due to its simplicity. Appropriate estimation of pathloss exponent (PLE) between a sensor node and an anchor node plays a key role in reducing position error in this RSS-based positioning. In the conventional researches, a sensor node directly uses the PLEs given by its neighboring anchor nodes, e.g., its nearest anchor node, to calculate its position. However, the PLE between a sensor node and an anchor node is usually different from those given by the anchor nodes, and accordingly results in the distance error in sensor node's positioning. In this paper, we propose the method how a sensor node estimates PLEs from the anchor nodes of interest by itself and calculates its position based on these self-estimated PLEs. In the proposed scheme, a sensor node recalculates PLEs depending on the estimated distances between itself and anchor nodes, and reproduces its position based on the recalculated PLEs. Through simulations, we show that our proposed positioning scheme outperforms the traditional scheme in terms of position error.

Analysis and evaluation of adaptive RSSI-based ranging in outdoor wireless sensor networks

“…Contrary to these techniques, many of the existing PLE estimation methods apply distance measurements and reference nodes. Some methods estimate the PLE in the localization phase iteratively and alternately with node locations [21,22]. They can use, e.g., the PLE from reference nodes as…”

“…an initial value to compute the node location [21], or even an unknown PLE [22], which is then used to recompute the PLE. In [23], the authors proposed a distributed, cooperative method that minimizes the cost function of unknown nodes' coordinates and PLEs using the iterative gradient descent approach.…”

“…RSSI data for the links was collected, once a minute, with two different transmit power levels, +3.0 dBm (P TX1 ) and −7.2 dBm (P TX2 ). The radio channel (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26) was changed every minute. In addition, the temperature readings for each node were measured once a minute with the SHT75 sensors.…”

A Received Signal Strength-based Primary User Localization Scheme for Cognitive Radio Sensor Networks Using Underlay Model-based Spectrum Access

“…However, the assumption of the linearity has the problem that can be ensured only in the particular environment. Junho et al [21] used an iterative PLE estimation method targeting a fixed PLE. Thus, if the fixed PLE has variations, the convergence time of the iterative method may largely increase.…”

“…Thus, if the fixed PLE has variations, the convergence time of the iterative method may largely increase. In addition to [21], the authors also considered the linearity of the PLEs similar to [19,20]. Hence, the localization scheme in [21] will encounter the same problem.…”