Soft detection with synchronization and channel estimation from hard quantized inputs in impulsive UWB Power Line Communications

Author(s):  
Andrea M. Tonello ◽  
Nicolangelo Palermo
2014 ◽  
Vol 960-961 ◽  
pp. 1308-1311
Author(s):  
Yi Pei Huang ◽  
Ya Jun Han ◽  
Bao Fan Chen

This paper introduces the power line communications channel estimation method based on sparse Bayesian regression, it is through the use of Bayesian learning framework that provides a sparse model in the presence of noise accurate channel estimation model. Improved channel estimation using the power line for the system to consider the frequency domain equalization (FREQ) transmitter and receiver, the bit error rate and comparing the two methods for generating various channel estimation techniques, and (BER) performance curves simulation the results show that the performance of the method is better than the previous method of least squares technique.


2014 ◽  
Vol 1046 ◽  
pp. 281-284 ◽  
Author(s):  
Xuan Liu ◽  
Da Peng Lin ◽  
Ye Shen He

In this paper, we address a channel estimation scheme for power line communication systems based on compressed sensing techniques. With the properly designed pilot symbols, the received signals at the receiver can be reconstructed from a set of random projections, benefiting from a reduced sampling rate. Moreover, we propose a novel channel estimation structure for PLC systems, which can be applied for appropriate system design. Eventually, simulation results demonstrate that the proposed algorithm outperforms other algorithms and reduces the sample rate significantly.


2008 ◽  
Vol 54 (3) ◽  
pp. 1074-1081 ◽  
Author(s):  
David Bueche ◽  
Patrick Corlay ◽  
Marc Gazalet ◽  
Francois-Xavier Coudoux

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