AI Summary & Key Takeaways
AI InsightThe simulations have declared that the performance of the proposed estimator is quite satisfactory,even when the noise is coloured.
📌 3 Key Takeaways
Abstract
Abstract: An adaptive channel estimation method, to be used in Power Line Communication systems with OrthogonalFrequency Division Multiplexing modulation, is presented in this paper. The proposed Maximum A-Posteriori basedestimator assumes that the channel is frequency selective and slowly time varying and estimates the subchannelcorrelations adaptively. The performance of the estimator is investigated by evaluating the Mean Square Error ofestimations. The simulations are done using measured channel data with additive white Gaussian noise assumption,which show that the proposed estimator has better performance compared to Maximum Likelihood estimation. Theperformance of the proposed estimator is also analysed under the assumption of colored noise, which is the commoncase in power lines. The simulations have declared that the performance of the proposed estimator is quite satisfactory,even when the noise is coloured.