Distributed Iterative Quantization for Interference Characterization in Wireless Networks

We consider the problem of estimating the distance to a device transmitting in the 2.4GHz ISM band that is interfering with users of an 802.11b wireless network. Accurate estimation of the distance enables a network designer to optimally configure transmit power levels and channel assignments of a wireless network. The estimate is made by a cluster of wireless sensor motes deployed along the edge of an 802.11b network. These motes perform a 1-bit quantization of the Received Signal Strength (RSS) using a dithered quantization framework. The quantized bits are transmitted over a Binary Symmetric Channel(BSC) to the Cluster Head (CH), which then uses a Maximum-Likelihood Estimation (MLE) technique to estimate the unknown parameter. We propose a framework in which the CH uses an iterative parameter estimation scheme in which it provides low overhead feedback to the motes to adjust their threshold values for the 1-bit dithered quantization process. Evaluation of the Root Mean Squared Error (RMSE) of this iterative scheme shows that it performs significantly better than iterative approaches in which all the motes use either identical thresholds or the non-identical thresholds proposed in [1], [2]. Our iterative scheme also more accurately tracks sudden changes in the distance to the interferer compared to previous approaches.