Iterative Channel Estimation and Impulsive Noise Mitigation Algorithm for OFDM-Based Receivers With Application to Power-Line Communications


This paper presents a completely unique iterative receiver used to mitigate the impact of impulsive noise (IN) on orthogonal frequency-division multiplexing (OFDM)-based baseband power-line communications. An adaptive threshold is mathematically derived for the detection of IN under a desired false alarm likelihood. This detection mechanism is then used to mitigate IN in 2 stages. Prior to the OFDM demodulation, a pre-IN mitigation block is employed to clip the stronger parts of the IN source. This preprocessing significantly reduces the power of the IN spreading into all subcarriers and, so, facilitates the detection of residual IN in the second stage. Once the OFDM demodulation, the proposed receiver iteratively estimates the channel impulse response and reduces IN sources that weren't detected by the pre-IN mitigation block. Post-IN mitigation involves the iterative reconstruction of residual IN, that is then subtracted from the received signal. Denoising is additionally applied to the estimated channel impulse response. Therefore, channel estimation and IN mitigation are mutually beneficial. Simulation results confirm that the proposed iterative receiver considerably improves the mean squared error of the channel estimation furthermore bit-error rate.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Iterative Receivers for Downlink MIMO-SCMA: Message Passing and Distributed Cooperative Detection - 2018ABSTRACT:The fast development of mobile communications requires even higher spectral potency. Non-orthogonal
PROJECT TITLE :Diagnosing and Minimizing Semantic Drift in Iterative Bootstrapping Extraction - 2018ABSTRACT:Semantic drift is a common problem in iterative information extraction. Previous approaches for minimizing semantic drift
PROJECT TITLE :Iterative Block Tensor Singular Value Thresholding For Extraction Of Low Rank Component Of Image Data - 2017ABSTRACT:Tensor principal component analysis (TPCA) is a multi-linear extension of principal component
PROJECT TITLE : Efficiently Promoting Product Online Outcome: An Iterative Rating Attack Utilizing Product and Market Property - 2017 ABSTRACT: The prosperity of on-line rating system makes it a popular place for malicious
PROJECT TITLE : On Fault Tolerance for Distributed Iterative Dataflow Processing - 2017 ABSTRACT: Large-scale graph and machine learning analytics widely use distributed iterative processing. Typically, these analytics are

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry