Adaptive Kalman Filtering for Local Mean Power Estimation in Mobile Communications

In this paper, we investigate the local mean signal estimation problem for wireless communications. Recently, it has been shown that the Kalman filtering approach results in better power estimates when compared to the traditional window based approaches for mean power estimation. In our work, we extend the Kalman filtering approach to adaptive Kalman filtering by combining the Kalman filtering with the window based filtering. Hence, Kalman filtering became available for practical use. The filter has been tested with field measurements and shown to outperform window based techniques.